Rapid screening for antibiotic resistance and treatment regimens

Abstract

A method is presented that uses impedance flow cytometry for rapid susceptibility testing of antimicrobial agents, including phages and antimicrobial peptides, and rapid analysis of antimicrobial-mediated serum bactericidal assays.

Description

[Technical Field]

[0001] Background of the Invention The present invention relates to methods of impedance flow cytometry, for example, the use of impedance flow cytometry to determine antimicrobial susceptibility. [Background technology]

[0002] Antimicrobial resistance (AMR) is the ability of microorganisms to evade, modify, or adapt to the adverse effects of antimicrobial agents used against them. Of particular concern is the increase and global spread of resistant bacteria, which is now recognized as a major threat to the health and wealth of the world's people. When an infection is suspected, physicians often immediately prescribe antimicrobials with the aim of providing effective treatment quickly. However, in many cases, antimicrobials are not needed or are inappropriate for the specific organism causing the infection. One notable problem is the treatment of bacterial infections with antimicrobials that are ineffective due to the presence of resistance mechanisms. This can mean that the infection persists, increases in severity, and possibly spreads to other patients. A major reason for the rapid prescription of potentially ineffective antimicrobials is that laboratory tests to check for antimicrobial resistance traits arrive too late when patients first receive treatment to be useful in informing antimicrobial prescribing.

[0003] Typically, antimicrobial susceptibility testing measures microbial growth in the presence of an antimicrobial agent in liquid culture or on solid agar plates. A common test, known as the disk diffusion test (or a quantitative variation of this testing principle called the Etest), involves growing a microbial culture overnight to obtain a sample, which is then placed on an agar plate. Disks or strips containing known concentrations of antimicrobial agent are placed on the agar plate, and inhibition of microbial growth near the antimicrobial-containing disk or strip is measured after a long incubation period. Broth microdilution methods measure the growth of microorganisms in liquid cultures containing different concentrations of antimicrobial agent to determine the antimicrobial concentration at which microbial growth is inhibited (known as the minimum inhibitory concentration, or MIC). Broth microdilution MIC methods can be performed using automated laboratory equipment. These traditional assays measure the growth of a population of microorganisms over time and take many hours to perform. Therefore, the results cannot be used to inform or guide prescriptions in the early stages of infection, when guidance is most critical.

[0004] As an alternative to these traditional tests that measure microbial populations, analyzing the optical properties of single microorganisms exposed to antimicrobial agents has been demonstrated to closely correlate with antimicrobial susceptibility measured in traditional tests, but within a shorter time frame of less than one hour (WO 2012 / 164547). Generally, a population of microorganisms is exposed to an antimicrobial agent for a set period of time, typically 30 minutes. The microorganisms are then washed by centrifugation to remove the antimicrobial agent and stained with a specific membrane-permeable fluorescent dye that can be used to indicate susceptibility to the agent. The optical properties of the microorganisms are measured using an optical flow cytometer, which detects light scattered from the microorganisms in the forward direction, indicating particle size, and the corresponding fluorescent signal of the microorganisms. The optical data is compared with data obtained from the same population of microbial samples that have been stained with the dye but not exposed to the antimicrobial agent. The difference in data from the two samples indicates whether the microorganisms are susceptible to the agent. Furthermore, exposure of the sample to a series of different antimicrobial concentrations is used to determine the minimum dose of antimicrobial agent required to effectively inhibit microbial growth. Optical cytometry has many drawbacks. The use of dyes typically requires one or more wash steps in the procedure, which limits the scope for miniaturizing and automating the testing procedure. Removal of the antimicrobial agent by washing before adding the dye interrupts the antimicrobial treatment at that point, thereby preventing continuous measurement of antimicrobial efficacy over time for a single sample. Optical cytometers are bulky, very expensive, and require manipulation techniques such as hydrodynamic and / or acoustic focusing to precisely position microorganisms within the optical analysis zone. Fluorescent dyes are also expensive. Therefore, optical cytometry is not well suited for analyzing antimicrobial susceptibility at the desired time point.

[0005] Therefore, new approaches are needed that can increase the speed and reduce the cost of antimicrobial susceptibility testing analysis, which in turn can guide appropriate antimicrobial prescribing. Summary of the Invention [Means for solving the problem]

[0006] Summary of the Invention Aspects and embodiments are set out in the accompanying claims.

[0007] Provided herein is a method for antimicrobial susceptibility testing, comprising preparing one or more samples of microorganisms suspended in an electrolyte, including a first sample of microorganisms exposed to one or more antimicrobial agents; passing the first sample through an impedance flow cytometer to obtain a first impedance signal representing one or more components of the impedance value of the microorganisms exposed to the antimicrobial agents; comparing the first impedance signal with a reference impedance signal; and determining the susceptibility of the microorganisms to the antimicrobial agents based on any difference between the first impedance signal and the reference impedance signal, wherein the antimicrobial agents are one or more selected from the group consisting of phage, serum component, immune system component, and antimicrobial peptide, and preferably the antimicrobial peptide is a membrane-permeable peptide, membrane-disrupting peptide, or pore-forming peptide antimicrobial. A reference signal can be obtained by preparing a second sample of the microorganisms exposed to the antimicrobial agents and passing the second sample through the impedance flow cytometer to obtain a second impedance signal representing one or more components of the impedance value of the exposed microorganisms. The reference signal may be a predetermined value for one or more components of the impedance value included in the first impedance signal, optionally the components being electrical size (in an embodiment, the X-axis on a scatter plot) and / or electrical opacity (in an embodiment, the Y-axis on a scatter plot). The reference impedance signal may be a threshold value, and determining the susceptibility may include comparing the first impedance signal to the threshold value.

[0008] According to aspects of certain embodiments described herein, there is provided a method of antimicrobial susceptibility testing comprising: preparing samples of microorganisms suspended in an electrolyte, the samples comprising a first sample of microorganisms not exposed to an antimicrobial agent and a second sample of microorganisms exposed to an antimicrobial agent; passing the first sample through an impedance flow cytometer to obtain a first impedance signal representing one or more components of the impedance value of the unexposed microorganisms; passing the second sample through the impedance flow cytometer to obtain a second impedance signal representing one or more components of the impedance value of the exposed microorganisms; comparing the first impedance signal with the second impedance signal; and determining the susceptibility of the microorganisms to the antimicrobial agent based on any difference between the first impedance signal and the second impedance signal, wherein the particles are microorganisms, and the microorganisms have been exposed to an antimicrobial agent selected from the group consisting of phages, serum components, immune system components, and antimicrobial peptides, and preferably the antimicrobial peptide is a membrane-permeating peptide, a membrane-disrupting peptide, or a pore-forming peptide antimicrobial.

[0009] According to aspects of certain embodiments described herein, a method includes flowing a sample of a fluid including particles suspended in an electrolyte along a flow channel; and applying electrical signals to current paths through the fluid, the current paths comprising at least a first current path, a second current path, a further first current path, and a further second current path, the electrical signals applied to the first current path and the further first current path having a frequency, magnitude, and phase, and the electrical signals applied to the second current path and the further second current path having a frequency and magnitude substantially equal to, and opposite phase to, the electrical signals applied to the first current path and the second current path; detecting a current in a first current path and a second current path; generating a first summed signal representing a sum of the currents detected in a further first current path and a further second current path; and obtaining a differential signal representing a difference between the first summed signal and the second summed signal, wherein the particles are microorganisms and the microorganisms have been exposed to an antimicrobial agent selected from the group of a phage, a serum component, an immune system component, and an antimicrobial peptide, preferably the antimicrobial peptide is a membrane-permeating peptide, a membrane-disrupting peptide, or a pore-forming peptide antimicrobial agent.

[0010] These and further aspects of particular embodiments are set forth in the accompanying independent and dependent claims. It will be understood that features of the dependent claims may be combined with each other, and that features of the independent claims may be combined in combinations other than those explicitly set forth in the claims. Furthermore, the approaches described herein are not limited to the particular embodiments as described below, but include and contemplate any suitable combination of features presented herein. For example, a method may be provided according to the approaches described herein that includes any one or more of the various features described below, as appropriate.

[0011] BRIEF DESCRIPTION OF THE DRAWINGS For a better understanding of the present invention and to show how it may be carried into effect, reference will now be made, by way of example, to the accompanying drawings in which: [Brief explanation of the drawings]

[0012] [Figure 1] FIG. 1 shows a schematic cross-sectional side view of an exemplary impedance flow cytometry device; [Figure 2] FIG. 2 shows a schematic cross-sectional side view of a portion of the apparatus of FIG. 1; [Figure 3] Figures 3(a)-(c) show graphs of current versus time and differential current versus time measured with the apparatus of Figures 1 and 2; [Figure 4] FIG. 4 shows a schematic cross-sectional side view of an electrode and circuit configuration for an impedance flow cytometer according to a first embodiment of an alternative electrode arrangement; [Figure 5] 5(a)-(c) show graphs of summed current versus time and differential summed current versus time measured by the method using the apparatus of FIG. 4; [Figure 6] FIG. 6 shows a schematic cross-sectional side view of an electrode and circuit configuration for an impedance flow cytometer according to a second embodiment; [Figure 7] FIG. 7 shows a schematic cross-sectional side view of an electrode and circuit configuration for an impedance flow cytometer according to a third embodiment; [Figure 8] FIG. 8 shows a schematic cross-sectional side view of an electrode and circuit configuration for an impedance flow cytometer according to another embodiment; [Figure 9] Figure 9(a) and (b) show schematic diagrams of the interaction of electric fields with cells at low and high frequencies; [Figure 10] 10(a), (b), (c), and (d) show exemplary scatter plots of impedance data recorded from bacterial cell samples at two frequencies using an impedance flow cytometry method according to an embodiment of the present disclosure, illustrating the antibacterial effects against susceptible and resistant bacterial strains; [Figure 11]11(a) and (b) show exemplary scatter plots of impedance data recorded from bacterial cell samples at two frequencies using an impedance flow cytometry method according to an embodiment of the present disclosure, illustrating the additive effect of an antimicrobial agent on susceptible bacteria. [Figure 12] 12(a) and (b) show exemplary scatter plots of impedance magnitude and phase data recorded from a bacterial cell sample at one frequency using an impedance flow cytometry method according to an embodiment of the present disclosure; [Figure 13] 13(a) and (b) show exemplary scatter plots of impedance magnitude and phase data recorded from a bacterial cell sample at two frequencies using an impedance flow cytometry method according to an embodiment of the present disclosure; [Figure 14] 14(a)-(f) show exemplary scatter plots of impedance data recorded from bacterial cell samples at two frequencies using an impedance flow cytometry method according to an embodiment of the present disclosure, illustrating the effect of different concentrations of antimicrobial agents on a susceptible bacterial strain; [Figure 15] 15(a)-(d) show graphs of the variation of several bacterial cell properties with the concentration of antimicrobial exposure obtained by impedance flow cytometry methods according to embodiments of the present disclosure; [Figure 16-1] FIG. 16 shows a sequence of scatter plots of impedance data continuously recorded over time from a single sample of bacteria exposed to an antimicrobial agent using an impedance flow cytometry method according to an embodiment of the present disclosure. Each plot represents a 1-minute window from time=0 to time=28 minutes. The Y-axis shows electrical opacity (|Z40MHz| / |Z5MHz|) from 0.6 to 1.0, marked in increments of 0.2. The X-axis shows electrical radius |Z1 / 3 5MHz| from 1.5 to 3, marked in increments of 0.5; [Figure 16-2]FIG. 16 shows a sequence of scatter plots of impedance data continuously recorded over time from a single sample of bacteria exposed to an antimicrobial agent using an impedance flow cytometry method according to an embodiment of the present disclosure. Each plot represents a 1-minute window from time=0 to time=28 minutes. The Y-axis shows electrical opacity (|Z40MHz| / |Z5MHz|) from 0.6 to 1.0, marked in increments of 0.2. The X-axis shows electrical radius |Z1 / 3 5MHz| from 1.5 to 3, marked in increments of 0.5; [Figure 17] FIG. 17 shows a schematic cross-sectional side view of an electrode and circuit configuration for an impedance flow cytometer according to an embodiment having differently oriented current paths; [Figure 18] FIG. 18 shows an exemplary scatter plot of impedance magnitude data obtained using an impedance flow cytometry method in a device such as the embodiment of FIG. 17; [Figure 19] Figure 19 shows a bar graph of the results of bacterial cell populations treated with antibiotics at predefined concentrations for susceptibility and resistance breakpoint analysis, measured using impedance flow cytometry; [Figure 20] Figure 20 shows a scatter plot of impedance data recorded from various bacterial cell samples exposed to various antibiotics at predetermined breakpoint assay concentrations, along with a bar graph of the corresponding cell population for each sample; [Figure 21] Figure 21 shows the time course of bacterial impedance flow cytometry profiles of A. baumannii strains (NCTC 13302) and B. non-susceptible (NCTC 10303) treated with phage Ab_2. The scatter plot shows the distribution of impedance measured for individual bacteria at 15 minutes (T15), 30 minutes (T30), 45 minutes (T45), 60 minutes (T60), 75 minutes (T75), and 90 minutes (T90). The Y-axis shows electrical phase (40 MHz) in 0.5 increments ranging from 0 to 1. The X-axis shows electrical radius (||Z|1 / 3 5 MHz|) in 0.5 increments ranging from 1 to 3.5. [Figure 22]Figure 22 shows the reduction in total cell number (A) and increase in cell size (B) for the sensitive strain (shown in gray on the right at each time point) compared to the resistant strain (shown in black on the left at each time point); [Figure 23] Figure 23 shows the effect of treating a susceptible population of microorganisms with a high phage concentration over a 1-hour time course. Bacterial impedance flow cytometry profiles were obtained at 0 (T0), 15 (T15), 30 (T30), 45 (T45), and 60 minutes (T60). Figure 23A shows the bacterial impedance flow cytometry profile obtained from a sample of the susceptible strain after treatment with a high phage concentration. Figure 23B shows the bacterial impedance flow cytometry profile obtained from a sample of the same susceptible strain that was not treated with phage. The Y-axis shows electrical phase (40 MHz) in 0.5 increments ranging from 0 to 1. The X-axis shows electrical radius (||Z|1 / 3 5 MHz|) in 0.5 increments ranging from 1 to 3.5; [Figure 24] Figure 24 shows the reduction in total cell number (A) and increase in cell size (B) for a susceptible bacterial strain treated with phage (shown in gray on the right at each time point) compared to the same strain without phage infection (shown in black on the left at each time point) over a 60 minute time course; [Figure 25A] Figure 25 shows bacterial impedance flow cytometry data used to determine phage susceptibility of potential clinical isolates. A. Scatter plot showing the distribution of impedance measurements obtained from individual bacteria of strains treated with phages Ab_1 (second column), Ab_2 (third column), and Pa_1 (last column) compared to the control (top row, no phage) after 90 minutes of treatment. The Y-axis shows electrical opacity (|Z40MHz| / |Z5MHz|) from 0.6 to 1.0 in increments of 0.2. The X-axis shows electrical radius |Z1 / 3 5MHz| from 1.0 to 3.5 in increments of 0.5. [Figure 25B]Figure 25 shows bacterial impedance flow cytometry data used to determine phage susceptibility of potential clinical isolates. B. Data analysis shows both the total cell count as a percentage of the control (top panel) and the number of cells within the outlined area as a percentage of the control (bottom panel) for each strain-phage combination: phage Pa_1 (left column); phage Ab_1 (middle column); and phage Ab_2 (right column); [Figure 26A] Figure 26 shows that different types of antimicrobial peptides induce rapid changes in bacterial impedance at supra-inhibitory concentrations but not at sub-inhibitory concentrations. Figure 26A shows the sensitivity of Escherichia coli (E. coli) NCTC 12923 to cationic AMP (cAMP) and an α-helical peptide (melittin), and Figure 26B shows the sensitivity of E. coli NCTC 13368. The scatter plots show the distribution of impedance measurements obtained from individual bacteria of peptide-treated strains compared to the control. The Y-axis shows electrical opacity (|Z40MHz| / |Z5MHz|) from 0.6 to 1.0 in increments of 0.2. The X-axis shows electrical radius |Z1 / 3 5MHz| from 1.0 to 3.5 in increments of 0.5. Data analysis shows both the total cell number as a percentage of the control (top panel) and the number of cells within the outlined area as a percentage of the control (bottom panel) for each strain-peptide combination. [Figure 26B]Figure 26 shows that different types of antimicrobial peptides induce rapid changes in bacterial impedance at supra-inhibitory concentrations but not at sub-inhibitory concentrations. Figure 26A shows the sensitivity of Escherichia coli (E. coli) NCTC 12923 to cationic AMP (cAMP) and an α-helical peptide (melittin), and Figure 26B shows the sensitivity of E. coli NCTC 13368. The scatter plots show the distribution of impedance measurements obtained from individual bacteria of peptide-treated strains compared to the control. The Y-axis shows electrical opacity (|Z40MHz| / |Z5MHz|) from 0.6 to 1.0 in increments of 0.2. The X-axis shows electrical radius |Z1 / 3 5MHz| from 1.0 to 3.5 in increments of 0.5. Data analysis shows both the total cell number as a percentage of the control (top panel) and the number of cells within the outlined area as a percentage of the control (bottom panel) for each strain-peptide combination. [Figure 27] (A) Scatter plot showing the distribution of impedance measurements after 2 hours of growth obtained from A. baumannii (NCTC 13302) untreated (307 cells within the gated region) or treated with phage at different multiplicities of infection: (B) MOI = 1, 144 cells within the gated region; (C) MOI = 0.1, 317 cells within the gated region; (D) MOI = 0.01, 333 cells within the gated region. The Y-axis shows electrical opacity (|Z40MHz| / |Z5MHz|) marked from 0.4 to 1.2 in increments of 0.2. The X-axis shows electrical radius |Z1 / 3 5MHz| marked from 1.0 to 3.5 in increments of 0.5. The gated region is the area enclosed by a contour enclosing 50% of the untreated population. [Figure 28] Figure 28 shows the variation in cell number compared to the untreated cell population (black, first column on the left) at A: 30 min (Y-axis: 0-10,000 cells within outline); B: 1 h (Y-axis: 0-1,600 cells within outline); C: 1 h 30 min (Y-axis: 0-2,000 cells within outline); D: 2 h (Y-axis: 0-350 cells within outline) for populations treated with an MOI of 1 (dark gray, second column from the left), an MOI of 0.1 (medium gray, third column from the left), and an MOI of 0.01 (light gray, right column). DETAILED DESCRIPTION OF THE INVENTION

[0013] Detailed Description Aspects and features of particular examples and embodiments are discussed / described herein. Some aspects and features of particular examples and embodiments may be implemented in a conventional manner and are not discussed / described in detail for the sake of brevity. Thus, it will be understood that aspects and features of the apparatus and methods discussed herein that are not described in detail may be implemented in accordance with any conventional techniques for implementing such aspects and features.

[0014] Disk diffusion, broth microdilution, and optical flow cytometry are examples of testing procedures for determining the susceptibility of microorganisms to antimicrobial agents. Such tests or assays can be referred to as antimicrobial susceptibility tests or testing (AST). This disclosure proposes the use of an alternative procedure for this and other purposes, using impedance flow cytometry. This technique uses an apparatus to measure the electrical properties, specifically the frequency-dependent impedance, of individual particles flowing within a microfluidic channel. It has been found that exposure to antimicrobial agents (antibiotics) can alter the impedance properties of suspensions of microorganisms (such as bacteria). The use of impedance flow cytometry to detect changes in the impedance of single microorganisms flowing through a microfluidic channel is proposed for determining the susceptibility of the microorganism to the antimicrobial agent or combination of antimicrobial agents being tested. The methods described herein can rapidly provide data regarding the susceptibility of the microorganism being tested (e.g., within 30 minutes, 1 hour, or 2 hours). The results provide the same information as currently used gold-standard tests, providing information on the antimicrobial agent's ability to kill or prevent the growth of microorganisms, allowing for faster conclusions about treatment options. The results also provide more information about the mechanism and speed of action of antimicrobial and population characteristics, which may enable resistance prediction. "Gold-standard" tests include routine culture-based methods, which require a minimum of 6-8 hours for both automated and automated microbiology, and more commonly 16-20 hours from initial culture for the development of colonies / plaques on plates, or 48-72 hours for slow-growing bacteria. Because each measurement reflects the characteristics of a single microorganism, the detection limit is improved over existing tests. The improved time-to-results of the methods described herein provides an advantage in tailoring antimicrobial therapy, such as phage therapy, for individual patients and can help ensure that antimicrobial agents, such as phages, are used only on susceptible clinical isolates.Bacteriophages offer an alternative therapy for the treatment of multidrug-resistant (MDR) infections, particularly those caused by Gram-negative bacteria. One challenge in using phage therapy is how to rapidly assess the susceptibility of a pathogen to treatment with a specific phage or a formulation containing multiple phages (also known as a phage cocktail), for example, to target isolates from the same species or a range of species. Time is particularly important for patients suffering from MDR infections. The methods of the present invention have the advantage of being able to rapidly identify the susceptibility of clinical isolates to antibacterial agents, such as phages, in, for example, less than or about 60 minutes, about 15 minutes, or more than 15 minutes.

[0015] For the purposes of this disclosure, an antimicrobial or antibacterial agent is considered to be any agent that kills or inhibits the growth of one or more strains of microorganisms.

[0016] Examples of antibacterial agents are antibiotics, antifungals, and antivirals. Antibiotics are agents that kill (bactericidal) or inhibit the growth (bacteriostatic) of bacteria. Antibiotics can act by one of many different mechanisms, including, but not limited to, disrupting the synthesis or integrity of microbial cell walls, blocking protein translation, preventing intracellular nucleic acid replication, repair, or maintenance, preventing the synthesis of essential molecules (e.g., folic acid, cholesterol), and disrupting membrane structure. Examples of antibiotic classes are aminoglycosides, ansamycins, azoles, carbacephems, carbapenems, cephalosporins, echinocandins, glycopeptides, lincosamides, lipopeptides, macrolides, monobactams, nitrofurans, oxazolidinones, penicillins, pleuromutilins, quinolones, fluoroquinolones, sulfonamides, tetracyclines, and trimethoprim, but other antibiotics and antibacterial agents are not excluded. Cefrosporins, penicillins, and carbapenems can be co-formulated with β-lactamase inhibitors to improve efficacy.

[0017] The antibacterial agent may exclude antibiotics, antifungals, and antivirals. The antibacterial agent may exclude one or more of aminoglycosides, ansamycins, azoles, carbacephems, carbapenems, cephalosporins, echinocandins, glycopeptides, lincosamides, lipopeptides, macrolides, monobactams, nitrofurans, oxazolidinones, penicillins, pleuromutilins, quinolones, fluoroquinolones, sulfonamides, tetracyclines, and trimethoprim. The antibacterial agent may exclude glycopeptides and lipopeptides. The antibacterial agent may include non-antibiotics.

[0018] Antibacterial agents can include viruses such as bacteriophages (also known as phages). Viruses such as bacteriophages are more specific than antibiotics and can target one specific strain of microorganism (e.g., bacteria). Thus, antibacterial agents can include two or more phages. The two or more phages can be presented in the form of a panel of individual phages or a mixture of different phages (also known as a phage cocktail). One or more phages can be tested. One or more cocktails of phages can be tested. Samples taken from patients during recovery may contain appropriate phages that can be used to cure other patients infected with the same strain.

[0019] Antimicrobial agents can include antimicrobial peptides, such as antibacterial peptides, e.g., membrane-permeable, membrane-disruptive, or pore-forming peptide antimicrobial agents. Antimicrobial peptides (sometimes called host defense peptides) can include bacteriocins, lantipeptides, pyocins, phage-derived endolysins, endopeptidases, polymyxins, and muralic proteins (e.g., altilisin). They can also include synthetic antimicrobial peptides based on repeating cationic amino acids (arginine or lysine) or other cationic compounds, such as polyamines (e.g., spermidine), or similar approaches. Antimicrobial peptides can be linear antimicrobial peptides, typically 20 to 50 amino acids in length, and can include pleurocidin and / or melittin. Linear antimicrobial peptides can be from 5, 10, 15, or 20 amino acids to 50, 70, or 100 amino acids in length. Peptides can be composed of L-amino acids, D-amino acids, β-amino acids, and combinations thereof. Also included are cyclic peptides and peptides with derivatization or amino acids not routinely found in proteins. Antimicrobial peptides can exclude cyclic peptides and / or peptides with derivatized amino acids or amino acids not routinely found in proteins. Antimicrobial agents can include components of the innate immune system, including chemokines and host defense peptides (including either whole or truncated derivatives of these molecules). Antimicrobial agents can include antibodies, such as monoclonal antibodies, e.g., species-specific monoclonal antibodies. Antimicrobial agents can include serum from a patient, e.g., a human patient, e.g., a patient who may be infected with drug-resistant bacteria or who has recovered from an infection by a microorganism. Antimicrobial agents can be one or more selected from the group consisting of phages, serum components, immune system components, and antimicrobial peptides; preferably, the antimicrobial peptide is a membrane-permeable peptide, a membrane-disrupting peptide, or a pore-forming peptide antimicrobial.The antimicrobial agent may be one or more selected from the group consisting of phages, serum components, immune system components, and antimicrobial peptides, preferably the antimicrobial peptide is a linear antimicrobial peptide, a membrane-permeable peptide, a membrane-disrupting peptide, or a pore-forming peptide, and / or the antimicrobial peptide consists of L-amino acids, D-amino acids, β-amino acids, and combinations thereof, more preferably the antimicrobial agent is not a glycopeptide or a lipopeptide.

[0020] For the purposes of this disclosure, a microorganism is considered to be a microscopic organism that may exist in its single-cell form or in colonies of cells. Examples of microorganisms include bacteria, viruses, and fungi (including yeasts and molds).

[0021] Antimicrobial agents, such as phages, can be prepared for clinical use. A single antimicrobial agent, such as phage Ab_1, phage Ab_2, or phage Pa_1, can be used. A panel of antimicrobial agents, such as a panel of phages, a set of phages known to target specific causative agents associated with a particular condition, such as a urinary tract infection, can be used. Each antimicrobial agent, such as a phage, can be mixed with a separate sample of one or more infectious agents. The panel of antimicrobial agents can be contained within a device containing multiple wells or channels that can be directly interfaced with an impedance cytometer. Each antimicrobial agent can be mixed with each infectious agent, and susceptibility can be measured, for example, by bacterial impedance flow cytometry to generate a susceptibility matrix. Data can be used to identify combinations of antimicrobial agents, such as phages, that can be used to simultaneously treat multiple infectious agents, such as multidrug-resistant isolates. Two or more phages (a "phage cocktail") can be mixed with the same sample of infectious agent. Preferred phages include, for example, lytic phages from the Myoviridae and / or Siphoviridae families. Antibiotic susceptibility and phage susceptibility impedance assays can be combined by mixing to identify synergistic combinations of phage and antibiotics that are highly effective in treating infections.Synergistic effects between phages from any of the known phage families (including, but not limited to, phages from the families Siphoviridae, Myoviridae, Podoviridae, Ackermannviridae, Inoviridae, Leviviridae, Microviridae, and Cystoviridae) can be observed with any antibiotic (including, but not limited to, aminoglycosides, cephalosporins, penicillins, carbapenems, tetracyclines, (fluoro)quinolones, oxazolidinones, macrolides, lincomycins, glycopeptides, sulfonamides, and pleuromutilins). Particularly preferred combinations include a lytic phage and an antibiotic that is generally impermeable to Gram-negative bacteria (eg, rifampicin, novobiocin, vancomycin, linezolid, fosfomycin).

[0022] The infectious agent (microorganism) is identified. Identification can include isolation from a clinical sample. Clinical samples can include urine, blood and / or other sterile site fluids, cerebrospinal fluid (CSFF), synovial fluid, or samples collected from wounds. The infectious agent can be assayed directly in the clinical sample. The clinical sample may undergo processing steps, such as centrifugation, cell lysis, or cell filtration, to remove cells (e.g., red blood cells and / or white blood cells and / or platelets). The clinical sample can be plated using standard microbiological techniques, for example, on selective plates for specific organisms. Identification can include the use of Maldi-Tof or one or more other bacterial ID systems. Bacterial ID systems include EPI strips, automated bacterial ID platforms (e.g., Vitek system, Biomerieux), traditional assay methods (Gram staining), metabolic tests (oxidase staining), and genotypic methods such as PCR using species-specific primers. Identification can also include tentative identification of the causative agent based on the patient's symptoms, e.g., Escherichia coli, Klebsiella pneumoniae, and / or Enterobacteriaceae such as Proteus mirabilis in the case of a urinary tract infection.

[0023] The microorganism may be a bacterium. To isolate or subculture bacteria from a sample, processes such as capturing bacteria on beads using physicochemical or biochemical principles, such as beads coated with polycationic or polyanionic beads, species-specific antibodies, or general bacterial capture ligands (e.g., mannose-binding lectins, polymyxin derivatives, vancomycin derivatives), may be used. Other capture or separation methods include those based on physical effects, such as mechanical filtration or capture, and acoustic, magnetic, electrical, or optical techniques. A sample of microorganisms, e.g., bacteria, e.g., collected from a plate, is mixed with phage. The mixture is incubated for, e.g., at least 10 minutes, at least 15 minutes, at least 20 minutes, about 30 minutes, about 45 minutes, up to 50 minutes, about 1 hour, or up to 90 minutes. Preferably, the sample is incubated for about 15 minutes. More preferably, the sample is incubated for 30 minutes. Most preferably, the sample is incubated for about 1 hour. The sample is evaluated in an impedance cytometer using any of the methods described herein. The sample is evaluated in an impedance cytometer using any of the methods described herein to obtain one or more impedance signals. In the impedance flow cytometry methods described herein, data, e.g., impedance measurements, are collected for individual particles, e.g., microorganisms such as bacteria. Thus, an impedance signal can include impedance measurements for one or more particles. An impedance profile is a set of impedance data or measurements for a set of particles, e.g., a population of bacteria. Incubation can be performed directly on the impedance cytometer (e.g., to determine a time course) or in an incubator with automated sample loading onto the cytometer. Samples can be incubated outside the cytometer and evaluated by the impedance cytometer at a set time (endpoint determination).Preferred microorganisms include multidrug-resistant (MDR) bacteria, such as members of the ESKAPE group (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, Enterobacter spp. or other members of the Enterobacteriaceae family, Escherichia coli), drug-resistant Neisseria gonorrhoeae, Stenotrophomonas maltophilia, or Burkholderia cepacia / cenocepacia complex, more preferably A. baumannii. baunannii and / or P. aeruginosa, such as one or more of: A. baunannii strains NCTC 10303, NCTC 13302, ATCC 17978, ATCC 17978 ColR, and P. aeruginosa strain PAO1.

[0024] A control sample of untreated microorganism can also be evaluated to generate reference data and a reference profile. Aspects of the microorganism's profile that indicate susceptibility to the phage are evaluated. The evaluation can include comparing the profile of the treated microorganism with the reference profile, including determining differences in the profiles. The evaluation can be performed automatically using software algorithms that use artificial intelligence and machine learning, or based on a simple scatter plot. The reference profile can be a profile of an untreated sample of the same organism. The reference profile can be a profile of a treated sample of the microorganism at an earlier time point. The reference profile can be a model profile, e.g., one previously obtained from a sample of the same organism, or an average or standard profile of the organism, e.g., one calculated from data previously obtained from multiple untreated or multiple treated samples.

[0025] Serial dilutions of phage can be used to evaluate the profile, mixing a known number of phage (defined as plaque-forming units) with a known number of bacteria. The lowest concentration of phage capable of altering the aspect of a microorganism's profile that exhibits susceptibility to the phage allows for the measurement of infection efficiency (sometimes called plating efficiency), which helps guide the number of phage required for treatment. This can be used in a similar manner to MIC determinations used with antibiotics to determine the minimum concentration that prevents bacterial growth. A fixed concentration of phage against bacteria can also be used in the test, with the concentration defined based on the number of phage that can be delivered and maintained at the site of infection in a patient. This is similar to the clinical breakpoint threshold used to determine bacterial resistance or susceptibility to antibiotics.

[0026] The evaluation can include determining electrical opacity, which can be measured by an impedance, e.g., |Z Highfrequency | / |Z lowfrequency | can be calculated from |Z Highfrequency | is measured at frequencies above 10 MHz, and |Z lowfrequency | is |Z 40MHz | / |Z 5MHz The evaluation may involve determining the electrical size. For example, the electrical radius may be calculated from the impedance, e.g., |Z 1 / 3 5MHz |. The evaluation may include determining a phase. The evaluation may include determining a percentage of a control population, e.g., a population of normal, untreated bacteria, e.g., the proportion of cells located outside a contour enclosing 95%. The evaluation may include determining a percentage of a control population, e.g., a population of normal, untreated bacteria, e.g., the number and / or proportion of cells located within a contour enclosing 95%. The evaluation may include determining the number and / or proportion of cells located within a contour enclosing 50% of the control population. The contour may enclose 50%, 75%, 80%, 90%, or 95% of the control population.

[0027] Bacterial impedance flow cytometry assays can be used to identify phages that can be used to target, for example, the pathogens listed in Table 4, column 1, in narrow-spectrum treatments for eradication of chronic infections, such as the chronic diseases listed in Table 4, column 3.

[0028] A method for performing a serum bactericidal assay is provided. The impedance flow cytometry method described herein can be used to assess the ability of serum, e.g., from a patient's blood, to kill a pathogenic microorganism of interest. The method can assess, for example, the level of antibodies or other components in serum that can kill the microorganism. Other components can include, for example, antibiotics or phages circulating in the blood of recovered patients. The antibodies can be naturally occurring or generated as a result of active or passive immunization. The assay can be used to assess serum killing in combination with one or more other antimicrobial agents, including, but not limited to, antibiotics and / or phages. For example, 5.5 x 10 per mL of serum can be used to assess serum killing. 5 A sample of microorganisms, e.g., bacteria, taken from a plate, is mixed with serum or a mixture containing serum and one or more antimicrobial agents, such as antibiotics and / or phages, optionally after incubation to increase the concentration of the microorganisms and / or dilutions to achieve a specific concentration of the microorganisms, such as colony-forming units (CFUs). The mixture is incubated, for example, for 10 minutes or more, 15 minutes or more, 20 minutes or more, up to 50 minutes, or preferably 1 hour. The sample is evaluated in the impedance cytometer using any of the bacterial impedance flow cytometry methods described herein. Reference or control samples of untreated or treated microorganisms taken early in the time course, e.g., within 10 minutes of mixing the microorganisms with the antimicrobial agent, can also be evaluated to generate reference data and a reference profile. Aspects of the microbial profile that indicate susceptibility to the antimicrobial peptide are evaluated.

[0029] A method for determining the effectiveness of antimicrobial peptides using impedance flow cytometry is provided. For example, a sample of microorganisms, e.g., bacteria, optionally harvested from a plate after incubation to increase the concentration of the microorganisms, is mixed with an antimicrobial peptide. The mixture is incubated, for example, for at least 20 minutes, 30 minutes, up to 50 minutes, or preferably 1 hour. The sample is evaluated in the impedance cytometer using any of the methods described herein. A control sample of untreated microorganisms can also be evaluated to generate control data and a control profile. Aspects of the microbial profile that indicate susceptibility to the antimicrobial peptide are evaluated. The antimicrobial peptide efficacy profile can be used in combination with antibiotic susceptibility testing to determine synergistic interactions. This may be particularly relevant when antibiotics are normally unable to enter Gram-negative bacteria and when combinations with antimicrobial peptides that are membrane-permeable peptides overcome this barrier to entry. Particularly effective combinations include cationic antimicrobial peptides or other membrane-permeable peptides used with antibiotics selected from the list including rifampicin, linezolid, fosfomycin, novobiocin, and vancomycin.

[0030] FIG. 1 shows a simplified, schematic, cross-sectional side view of a first embodiment of an apparatus for impedance flow cytometry, which has a relatively simple format. This apparatus is typically constructed as a microfluidic device, formed from various layers deposited on a substrate and patterned using techniques such as photolithography to form the required structures. The field of microfluidics concerns the behavior, control, and manipulation of fluids confined or restricted on a small scale, typically submillimeter, or in other words, submicrometer, scale. In biological and medical fields and other fields of endeavor, microfluidic devices constructed from layers on a substrate for sample testing purposes are sometimes referred to as "lab-on-a-chip" devices. In the example of FIG. 1, device 10 includes a microfluidic flow channel 12 formed in a layer 14 of photoresist material, such as SU8, an epoxy-based negative photoresist sandwiched between a bottom layer 16a and a top layer 16b of glass material. An opening in top glass layer 16a defines an inlet 18 to channel 12 and an outlet 20 from channel 12. A fluid sample 22 is fed into the channel 12 at the inlet 18 and flows along the channel 12 to the outlet 20 (shown by the dotted arrow in FIG. 1 ), where the fluid sample is removed or discharged as waste 24 or collected for further analysis. The sample 22 can be provided into the channel 12 in any convenient manner, such as by injection from a syringe 26 into the inlet 18. Sheath flow may or may not be used to center particles within the bore or orifice of the channel. Other mechanisms, such as dielectrophoresis, acoustic, inertial, or viscoelastic techniques, can be used to focus particles in the flow.

[0031] The sample 22 contains particles that can be cells, bacteria, microorganisms, or other biological particles (e.g., algae, exosomes, viruses, or vesicles) or non-biological particles (e.g., droplets, beads, colloids, dust, or metal fragments) suspended in an electrolyte (electrolyte solution), depending on the nature of the test being performed. In the case of AST, the particles are microorganisms that may or may not be exposed to an antimicrobial agent. To accommodate the passage of cells, the channel can have a cross section transverse to the flow direction (from inlet to outlet) of about 40 μm height and about 40 μm width. More typically, channel dimensions can range from 1 to 100 μm. The cross section can be square or non-square.

[0032] The device 10 further includes first and second pairs of electrodes fabricated on the bottom and top walls of the channel 12. Each pair of electrodes includes a voltage electrode 30 and a measurement electrode 32. In the illustrated example of FIG. 1, the voltage electrode 30 is on the top wall of the channel 12, and the measurement electrode 32 is on the bottom wall of the channel 12, although these positions may be reversed. The first electrode pair is located at an upstream position within the channel 12, and the second electrode pair is located at a downstream position, such that particles in the sample pass through the first electrode pair before passing through the second electrode pair. The electrodes can have dimensions on the order of 1 to 100 μm, e.g., 10 to 40 μm, for analyzing microorganisms and bacteria, although larger or smaller sizes are possible depending on the channel size.

[0033] The voltage electrodes 30 are driven by a single voltage source 34 capable of generating one or more frequency components f1, f2, f3.... Thus, both voltage electrodes 30 provide the same voltage, approximately equal in magnitude, frequency, and phase. The two electrodes 30, 32 of each pair provide or define a current path across the flow channel 12 from the voltage electrode 30 to the measurement electrode 32 in the presence of the electrolyte of the sample 22 flowing within the flow channel 12. Current flowing through these current paths is detected at the measurement electrode 32. The current I1 detected at the first measurement electrode and the current I2 detected at the second measurement electrode are each sent to a separate current-to-voltage converter 34. The converter outputs are sent to a differential amplifier 36 to obtain a differential signal representing the difference between the currents in the two current paths, i.e., I2 - I1 (or, if preferred, I1 - I2). Additional electronics (e.g., circuitry, lock-in amplifier 38, processor 40) receive the differential signal and determine an impedance measurement therefrom. This output or impedance signal can separate the impedance measurements according to real (Re) and imaginary (Im) components, or preferably according to components of magnitude |Z| and phase θ. Particles passing between the electrodes of an electrode pair change the current detected at the measurement electrode, which is reflected in the final impedance signal. Therefore, the presence of particles, and their properties, can be inferred from the impedance signal.

[0034] The inclusion of two pairs of electrodes results in two measurable currents, allowing for a differential mode of operation as described above, reducing noise and artifacts. The purpose of differential signaling can be understood with reference to Figures 2 and 3.

[0035] FIG. 2 shows a schematic enlarged view of a portion of the device of FIG. 1, including two electrode pairs positioned across the flow channel 12. Particles 42, which represent microorganisms in an AST procedure, are suspended in the fluid flowing along the channel 12. FIG. 3 shows a graph of the detected current over time during an impedance measurement. FIG. 3(a) shows the current I1 detected by the first measurement electrode 32a. FIG. 3(b) shows the current I2 detected by the second measurement electrode 32b. FIG. 3(c) shows the differential signal obtained from a differential amplifier (or other circuitry capable of determining a differential signal), representing the difference between the two currents I2-I1.

[0036] At time t0, the particle 42 is within the channel but has not yet encountered an electrode. Therefore, both measurement electrodes 32a, 32b detect substantially the same, non-zero current because the same (nominal) voltage is supplied to both current paths. Therefore, the differential signal is substantially zero. Later, at time t1, the particle 42 passes between the electrodes 30a, 32a of the first electrode pair. This disrupts current flow in the first current path, causing the detected current I1 to drop, as shown in FIG. 3(a). The second current I2 is largely unaffected by the particle 42. Therefore, as shown in FIG. 3(c), the differential signal I2-I1 becomes positive as the particle 42 passes through the first electrode pair 30a, 32a. Then, at time t2, the particle is midway between the first electrode pair 30a, 32a and the second electrode pair 30b, 32b; therefore, both currents are approximately equal again, and the differential signal returns to zero. At time t3, the particle 42 reaches the second electrode pair 30b, 32b and interrupts the flow of current in the second current path. Thus, at t3, the first current I1 has its full value (see FIG. 3(a)), the second current I2 has a reduced value (see FIG. 3(b)), and the differential signal becomes negative (see FIG. 3(c)). At time t4, the particle 42 has flowed out of the measurement region or zone defined by the electrodes, neither current path is affected by the particle 42, and the differential signal is again zero. Appropriate processing of the actuation signal can be performed to estimate the impedance of the particle. The size, structure, shape, and composition of the particle determine its impedance characteristics and therefore how it affects the current flow defined by the electrode pair. The current in the pathway and its effect on the differential signal are determined. Exposure of a microorganism to an antimicrobial agent to which the microorganism is susceptible alters the size, structure, shape, and / or composition of the microorganism, such that its impedance characteristics are altered. This is reflected in the differential signal. Therefore, comparison of the differential signal, or the impedance signal derived from the differential signal, from a sample of microorganisms exposed to an antimicrobial agent with that from a sample of microorganisms not exposed to an antimicrobial agent can indicate whether the microorganism is susceptible to the agent. Thus, AST can be achieved using impedance flow cytometry.Certain cellular properties altered by antimicrobial treatment exhibit frequency-dependent responses. Therefore, utilizing voltages with appropriate single or multiple frequency components and processing the differential signal to extract impedance responses at different frequencies can reveal further information about susceptibility. Impedance flow cytometry offers advantages over other techniques for AST. For example, it is much faster than disk diffusion and broth microdilution AST and does not require a priori knowledge of the microorganism. Furthermore, this method does not require the addition of expensive dyes frequently used in optical cytometry, nor does it require the wash steps required after exposing microorganisms to antimicrobial agents. Therefore, impedance flow cytometry can be cheaper and more rapid than other techniques for AST. It can also be performed in the presence of antimicrobial agents, allowing time-dependent changes to be determined.

[0037] The currents in the two current paths are typically in the range of 1 to 10 mA, depending on the conductivity of the suspending electrolyte, the dimensions of the channel and electrodes, and the applied voltage signal. However, the change in current generated by a passing particle the size of a microbial or bacterial cell (smaller than a mammalian cell) is approximately 1 μA to 1 nA, i.e., within the range of approximately 1 part in 1,000 to 1,000,000 (note that the current plots in Figures 3(a)-(c) are not to scale). Therefore, the differential signal has a small magnitude and is relatively susceptible to noise. To maximize the signal-to-noise ratio of the differential signal, the voltage applied to the voltage electrodes can be as high as possible, maximizing the gain in the current-to-voltage converter. However, as the applied voltage increases, I1 and I2 each increase proportionally, which leads to clipping in the current-to-voltage converter and differential amplifier. Overall, nonzero current limits the maximum usable voltage and gain, which in turn limits the sensitivity of the device. Another approach to measuring microorganisms using impedance flow cytometry is to reduce the channel size to shorten the current path between the electrodes, so that small microorganisms have a proportionally larger effect on the detected current (because of their larger size relative to the channel size). However, narrower channels are more prone to blockage and also increase the backpressure within the channel, which scales with the fourth power of the channel size.

[0038] Therefore, impedance flow cytometers such as the example shown in Figure 1 have some limitations when measuring small particles, such as microbial and bacterial samples, for AST. Nevertheless, useful AST data can be obtained. Microfluidic flow past the electrodes allows for the detection and measurement of individual microorganisms, resulting in microbial enumeration, obtaining data on individual particles within a population of microorganisms in a sample, and analyzing the entire population. Various measurement techniques for AST are described in more detail below with respect to other example impedance flow cytometers; these can also be implemented using devices such as those shown in Figure 1 or other impedance flow cytometry devices.

[0039] This disclosure describes an example of an alternative design for an impedance flow cytometer that can provide improved sensitivity and performance. It can be used in a method for accurately measuring samples containing small particles such as bacteria and / or cells (or indeed, any biological or non-biological particle) in a large-diameter channel (although smaller channel sizes are not excluded). The device includes electrodes arranged to generate a current path through the microfluidic channel, the electrodes configured and driven to provide improved measurement sensitivity. Impedance flow cytometry can therefore be used for AST and other measurements, tests, and assays for bacterial particles as well as other biological and non-biological particles. However, this device has much broader applications and can be used to obtain impedance information about any type of particle that can be suspended in an electrolyte solution and flow through the channel past appropriately configured electrodes.

[0040] Figure 4 shows a schematic cross-sectional side view of a flow channel with electrodes, according to an example arrangement. The channel and electrodes may be embodied in a microfluidic chip structure such as that shown in Figure 1, although other structures and configurations may alternatively be used. Channel 12, in this example, has a total of eight associated electrodes. Each electrode is on the interior surface of flow channel 12 so as to contact the sample fluid flowing within flow channel 12. Alternatively, the electrodes may be spaced slightly apart from the electrolytic sample fluid.

[0041] The electrodes are configured as a first electrode group 50 and a second electrode group 52. The electrodes are configured as either signal electrodes or measurement electrodes for applying an electrical signal (current or voltage) and are arranged in pairs to provide a current path through the fluid flowing within the channel 12. Each of the first electrode group 50 and the second electrode group 52 provides a first current path from the signal electrode to a measurement electrode and a second current path from a different signal electrode to a measurement electrode. In this example, each of these electrodes is a separate element. Thus, each electrode group includes four electrodes, for a total of eight electrodes. The first electrode group 50 includes a first signal electrode 60a above the channel 12 that forms a first current path I3 with a first measurement electrode 62a below the channel 12, and a second signal electrode 64a above the channel 12 that forms a second current path I4 with a second measurement electrode 66a below the channel 12. The second electrode group 52 comprises a further first signal electrode 60b above the channel 12 that forms a further first current path 16 with a further first measurement electrode 62b below the channel 12, and a further second signal electrode 64b above the channel 12 that forms a further second current path 17 with a further second measurement electrode 66b below the channel 12. In this example, the electrodes are arranged in pairs along the flow channel length, such that the further second current path is downstream of the further first current path, which is downstream of the second current path, which is downstream of the first current path.

[0042] Within the first electrode group 50, the first signal electrode 60a is driven with a first voltage +V having a particular magnitude, phase, and frequency composition (one or more frequencies). In contrast, the second signal electrode 64a is driven with a second voltage −V having the same magnitude and frequency composition as the first voltage +V but 180° (π radians) out of phase with the first voltage.

[0043] The signal electrodes of the second electrode group 52 are driven with the same voltage as the corresponding signal electrodes of the first electrode group 50. Thus, the first further signal electrode 60b is driven with +V and the second further signal electrode is driven with −V, the same magnitude and frequency as the first and second voltages of the first electrode group 50. In the embodiment of Figure 4, this is achieved by supplying the first signal electrode 60a and the first further signal electrode 60b from a first voltage source 70 that generates +V, and supplying the second signal electrode 64a and the second further signal electrode 64b from a separate second voltage source 72 that generates −V.

[0044] It should be noted that absolute identical magnitude and frequency are not required, and some small differences are likely to occur in real-world conditions. Thus, terms such as "same" and "identical" in this context are not intended to be limiting and to include configurations in which the voltage characteristics are similar or approximately, substantially, or nominally the same, for example, within boundaries that one skilled in the art would understand to be acceptable for achieving a significant output signal as described herein.

[0045] Likewise, a phase difference of exactly 180° is not required, and the phases may differ by other amounts in the region of 180°. Thus, the phases of the two voltages may be considered to be "opposite," which is intended to include configurations in which the phase difference is close to, approximately, substantially, or nominally 180° (π radians), within the bounds that one skilled in the art would understand to be acceptable for achieving a significant output signal as described herein.

[0046] In this example, the signal electrodes can be considered voltage electrodes because they are driven with a specified voltage from a voltage source. In other examples, the signal electrodes can be driven with a particular current from a current source. Thus, the term "signal electrodes" is intended to include both alternatives, such that these electrodes provide an electrical signal having a frequency, magnitude, and phase difference as described and can be a voltage signal or a current signal. In any of the various examples, the voltage source and voltage electrodes can be replaced with a current source and current electrodes, or vice versa. Similarly, the application of a voltage can be understood more generally as the application of an "electrical signal," which can be a voltage or a current depending on the choice of power source.

[0047] The measurement electrodes are configured with circuitry that generates a differential signal indicative of the difference between measurements from the first electrode group 50 and the second electrode group 52. As shown in FIG. 4 , this is accomplished in this example by summing or combining a current I3 detected in a first current path (by the first measurement electrode 62a) with a current I4 detected in a second current path (by the second measurement electrode 66a) to generate a summed signal I5. This first summed signal I5 from the first electrode group is sent to a current-to-voltage converter 34a. Similarly, a current I6 detected in a further first current path (by the further first measurement electrode 62b) is summed or combined with a current I7 detected in a further second current path (by the further second measurement electrode 66b) to generate a summed signal I8. This second summed signal I8 from the second electrode group is sent to another current-to-voltage converter 34b. Note that in an alternative configuration, the circuitry may be configured to perform a current-to-voltage conversion before the summing or combining. In either case, a first summed signal I5 representing the sum of the currents in the first and second current paths of the first electrode group 50 and a second summed signal I8 representing the sum of the currents in the first and second current paths of the second electrode group 52 are sent to further circuitry configured to determine a differential signal representing the difference between the first and second summed signals. In the embodiment of FIG. 4, this includes a differential amplifier 36. The differential signal can then be processed using appropriate processing circuitry or electronics to calculate from the differential signal an impedance signal indicative of the impedance properties or characteristics of the sample fluid, which necessarily includes the impedance properties or characteristics of any particles in the sample fluid. From this, the effect of an antimicrobial agent on microorganisms in a sample fluid can be identified by comparing the impedance measurements with those from samples of the same microorganisms that have not been treated with the antimicrobial agent or that have been treated with different types or amounts of antimicrobial agent.For example, the differential signal can be input to a processor configured to process the differential signal for purposes of determining fluid and / or cell impedance signals, impedance values, impedance properties and characteristics, and / or cell counts, as described further herein and below. The circuitry and processing can be implemented using any suitable configuration or combination of hardware, firmware, and software, including simple electrical connections, logic gates, amplifiers, and a central processing unit. A single processor or similar processing electronics or circuitry can be used to process multiple differential signals obtained from multiple flow channels with associated electrodes, which may be implemented, for example, on a single substrate or chip. Devices configured in this manner allow for easy simultaneous measurements of multiple samples. In the context of microbial testing, this may allow a reference sample of untreated microorganisms to be measured simultaneously with a treated sample, or multiple samples of a specific microorganism to be tested with different antimicrobial agents, or multiple samples of a specific microorganism to be tested with different concentrations of the same antimicrobial agent to determine the so-called minimum inhibitory concentration. The derivation of the actuation signal can be understood from Figure 5, which shows graphs of current versus time for two summed signals (a) and (b) and the corresponding actuation signal (c).

[0048] FIG. 4 shows a particle 42, such as a bacterial cell, in flow channel 12, located upstream of a first set of electrodes 50 and about to enter a measurement region defined by the electrodes. By time t5, particle 42 has passed all of the electrodes and exited the measurement region. The graph in FIG. 5 shows various signals at subsequent times t1-t4, prior to t0 and t5. For convenience and simplicity, the fluid sample may have a cell concentration and flow rate along the fluid channel intended to provide only one particle at a time within the measurement region, which is the zone where the electric field of the electrodes resides.

[0049] At time t0, the particle 42 is outside the measurement region and does not interact with any of the current paths. Therefore, in the first electrode group 50, the first measurement electrode 62a detects a current I3 in the first current path that is equal in magnitude to but opposite in phase to the current I4 in the second current path detected by the second measurement electrode 66a. Therefore, I3 and I4 cancel each other, and their sum is zero (or nearly zero, given the slight difference in the electrical signals provided by the signal electrodes), providing a zero first summed signal I5 at time t0, as shown in FIG. 5(a). Similarly, in the second electrode group 52, the current I6 in the additional first measurement electrode 62b is equal but opposite to the current I7 in the additional second measurement electrode 66b, and as a result, their sum is also nearly zero, providing a zero second summed signal I8, as shown in FIG. 5(b). Therefore, at time t0, the differential signal I8-I5 is also zero, as shown in FIG. 5(c). Therefore, the "background" signal measured by the device is essentially zero in the absence of particles and is obtained from the difference between the two zero-value measurements. Therefore, the voltage applied to the voltage electrodes can be increased to high values ​​without the detected signal being clipped in the transducer 34 or differential amplifier 36, and measurement sensitivity can therefore be maximized within the capabilities of the voltage source.

[0050] At time t1, the particle is between the first signal electrode 60a and the first measurement electrode 62a, thus blocking the flow of current in the first current path. Therefore, I3 is reduced. Current I4 in the second current path between the second signal electrode 64a and the second measurement electrode 66a remains the same as before. Therefore, the first summed signal I5, which is I3 + I4, is also reduced. The second summed signal I8, which is I6 + I7 from the second group of electrodes, remains near zero because no particle is present in either of these current paths. Therefore, the differential signal I8 - I5 becomes positive due to the reduced value of I5. At time t2, the particle 42 has moved between the second signal electrode 64a and the second measurement electrode 66a. Current I3 in the first current path returns to its previous value, and current I4 in the second current path is reduced due to the presence of the particle 42. However, recall that the second signal electrode has a negative drive voltage, so the first sum signal I5 = I3 + I4 becomes positive, as shown in Figure 5(a). The second sum signal I8 remains approximately zero. Therefore, the differential signal I8 - I5 becomes negative at time t2.

[0051] At time t3 and thereafter at time t4, a particle enters the second electrode group 52, interacting with a first additional current path I6 at t3 and then with a second additional current path I7 at t4. Because the first additional current path I6 has the same voltage supply as the first current path I2, and the second additional current path I7 has the same voltage supply as the second current path I4, the second summed signal follows the same shape at times t3 and t4 as the first summed signal did at times t1 and t2, becoming negative at t3 and positive at t4. Meanwhile, the first summed signal I5 remains zero during these times because no particles are present in the portion of the measurement area corresponding to the first electrode group. Thus, as shown in FIG. 5(c), the differential signal I8-I5 becomes negative at t3 and then becomes positive at t4.

[0052] At time t5, the particle has left the measurement region, so all four current paths are undisturbed: both summed signals are essentially zero, giving a zero-valued differential signal as at time t0.

[0053] Note the particular shape of the curve followed by the differential signal, shown in Figure 5(c). The sequential arrangement along the channel length of the four pairs of electrodes with two electrode groups 50, 52, along with the alternating arrangement of positive and negative voltages on the signal electrodes along the channel length, gives a corresponding differential signal that exhibits positive, then negative, then more negative than positive characteristics over time as the particle passes along the measurement region. This shape is more distinct relative to noise than the differential signal from the device of Figure 1 and can therefore be more easily distinguished (using signal processing techniques). This improves the signal-to-noise ratio, further improving sensitivity.

[0054] The differential signal may alternatively, if preferred, be calculated as I5 - I8, i.e., the first summed signal minus the second summed signal. In either case, the differential signal represents the difference between the summed signals, and the impedance characteristics of the particle can be determined therefrom. This is also applicable to the examples described further below.

[0055] This electrode configuration (and similar configurations that achieve the same results) and its improved performance allow for meaningful impedance measurements to be obtained for small particles, such as bacteria, flowing within a large channel. This reduces the risk of channel blockage, making such devices more useful in real-world environments and situations. Bacterial cells typically range in size from 0.2 to 2 μm. By "large channel," we mean that the channel dimensions in a plane transverse to the fluid flow direction are in the range of about 10 to 50 μm, e.g., 20 μm. As an example, the channel can have a square cross-section (e.g., resulting from layered construction and formation by photolithography) with a substantially equal width and height of about 40 μm. Alternatively, the channel may have a height of about 10 to 50 μm, e.g., about 20 μm, perpendicular to the plane of the substrate on which the device is formed and the flow direction, parallel to the current flow channel from the voltage electrode to the measurement electrode, and the transverse (width) dimension is larger. Other dimensions can also be used, such as channels with smaller dimensions in the range of 100-1000 µm, suitable for measuring across cells of approximately 10 µm, or even larger channels that can accommodate millimeter-scale particles.

[0056] Other electrode configurations can be used to obtain the same or similar signals that can estimate the impedance characteristics of particles in the sample fluid. A variety of configurations are possible, including first and second groups of electrodes providing first and second current paths, each driven with approximately equal but approximately opposite voltages. Within a group, the first and second current paths may be at different positions along the flow direction of the channel, as in FIG. 4. The first and second groups of electrodes may also be at different positions along the flow direction of the channel, as in FIG. 4. The electrodes in each group do not need to be physically grouped together, but may be distributed among the electrodes in other groups.

[0057] FIG. 6 shows a schematic cross-sectional side view of a second embodiment including the same elements as FIG. 4. Thus, eight electrodes are included, including four signal electrodes and four measurement electrodes arranged in four pairs across flow channel 12. However, in this embodiment, the signal electrodes in each electrode group are arranged alternately along the flow channel. Thus, in sequence along flow channel 12, the measurement region includes first a first signal electrode 60a and its first measurement electrode 62a providing a first current path I3; second a first signal electrode 60b and its further first measurement electrode 62b providing a further first current path I6; third a second signal electrode 64b and its further second measurement electrode 66b providing a further second current path I7; and finally a second signal electrode 64a and its second measurement electrode 66a providing a second current path I4. The first current path I3 and the second current path I4 are combined for a first summed signal I5, and the further first current path I6 and further second current path I7 are combined, as before, for a second summed signal I8. The time evolution of the differential signal for a particle traversing the measurement region will have a different shape than shown in Figure 5(c) - it will contain positive, then negative, then positive, then negative features, but can be distinguished from noise by appropriate filtering and / or signal processing.

[0058] Both the embodiments of Figures 4 and 6 include separate voltage sources (or current sources) for supplying a first electrical signal to the first signal electrode of each group and an opposite second electrical signal to the second signal electrode of each group, the signal electrodes being connected to one side of the voltage source and the other side to ground.

[0059] Figure 7 shows a schematic cross-sectional side view of an alternative embodiment that is simplified by using a single voltage source to drive all of the signal electrodes. This example has eight electrodes arranged in the same manner as the embodiment of Figure 6. A single voltage source 71 drives all of the signal electrodes. The first signal electrode 60a, 60b of each electrode group is connected to the positive side of voltage source 71 and receives +V, and the second signal electrode 64a, 64b of each electrode group is connected to the negative side of voltage source 71 and receives -V.

[0060] As mentioned above, the device may be driven using a voltage or current applied to the signal electrodes. FIG. 8 shows an example device configured similarly to the embodiment of FIG. 4, but using a current source instead of a voltage source. The components are otherwise the same and will not be described in detail here. A first current source 80 provides a current having a magnitude, phase, and frequency composition to the first signal electrodes 60a, 60b of each of the first and second electrode groups 50, 52. A second current source 82 provides a current having substantially the same magnitude and phase to the second signal electrodes 64a, 64b of each electrode group 50, 52, but which is negative in that it has an opposite or nearly opposite phase compared to the current from the first current source 80 (the phase difference between the two currents is approximately 180° or π radians). Voltages V1 and V2, representing the summed signals from the measurement electrodes 62a, 66a, 62b, 66b of each electrode group 50, 52, are input to a differential amplifier 36 to determine a differential signal.

[0061] Other configurations for the electrodes and resulting current paths are possible. Typically, the electrodes are located above and below the flow channel due to constraints of conventional fabrication of layered microfluidic structures, but this is not required for operation, and devices may be configured with electrodes arranged around the flow channel in other orientations. In one example, the positive and negative signal electrodes may be arranged adjacently as in the example of FIG. 6, or, as opposed to the arrangement of FIG. 6, a first group of measurement electrodes may be arranged as two central measurement electrodes and a second group of measurement electrodes may be arranged as two outer measurement electrodes. All of the previous examples have provided signal electrodes at the top of the flow channel and measurement electrodes at the bottom of the flow channel. However, this is not a limitation, and either of the electrodes may be arranged in any position, perhaps according to convenience in connecting them to a voltage or current source (electrical signal source) and measurement circuitry. For example, one or more pairs of signal and measurement electrodes may be arranged in an opposite manner, with the measurement electrodes above the channel and the signal electrodes below the channel. Furthermore, individual electrodes may be combined into a larger electrode that performs the functions of two individual electrodes, for example, if the electrodes are physically adjacent. Consider the example of FIG. 4 , where the first and second measurement electrodes in the first electrode group are adjacent, and the additional first and second measurement electrodes in the second electrode group are adjacent and downstream from the first and second measurement electrodes. This allows the first and second measurement electrodes to be replaced with a combined single electrode that collects current from both the first and second current paths, so that its output is already a combined or summed signal from the first electrode group. Similarly, the additional first and second measurement electrodes can be replaced by a combined single electrode that outputs a summed signal representing the first and second current paths of the second electrode group. Signal electrodes may also be combined into a single larger electrode. Within the electrode groups described above, the signal electrode includes two electrodes that apply different and opposite electrical signals (voltages or currents) to the two current paths of the group. Therefore, it is not possible to combine signal electrodes within a group.However, the same voltage or current (nominal) is applied to corresponding positive and negative signal electrodes in the two different electrode groups, providing coverage where the signal electrodes are combined or shared across the electrode groups. Thus far, the embodiments have included paired electrodes to provide a current path through the fluid channel in a direction generally transverse to the fluid flow direction, achieved by arranging the paired electrodes on opposite sides of the channel. However, this is not required, and the current path may be otherwise arranged in any configuration that allows suspended particles to interact with the electric field emanating from the voltage electrodes, thereby modifying the current flow within the current path. For example, the electrodes may be arranged such that signal and measurement electrodes are alternately arranged along the upper and lower sides of the channel, but are positioned opposite electrodes of the same type. Thus, signal electrodes that generate the same electrical signal are opposite each other, and the electric field is directed toward adjacent measurement electrodes along the length of the channel. Such a configuration provides a current path that is substantially along or parallel to the direction of fluid flow through the channel. The electrodes may be planar, which is convenient in chip-based devices fabricated in layers, but is not required. For example, the electrodes may be formed as rings or collars which in turn surround the channels, which may be of circular or oval cross section, for example formed from pipes or tubes.

[0062] In further embodiments, the number of electrodes can be increased to provide additional current paths. This increases the unique nature of the differential signal pattern, facilitating its isolation from noise and thereby improving sensitivity. The number of electrode groups can be maintained at two, with extra electrodes within each group providing additional first and second current paths. A particle impedance signal can be extracted from peak and trough height-related features in the sum signal and / or differential signal. This can be achieved, for example, by measuring the amplitude of the peaks and / or troughs or by matching the signal shape to a template obtained for particles with known characteristics. The sequence of peaks and troughs in the sum signal and / or final differential signal can be designed by selecting the relative sequence of the signal electrodes. Signal processing mathematics indicates that some signal shapes are more unique than others, and as a result, an improved signal-to-noise ratio can be obtained by appropriate sequencing of electrodes along the flow channel.

[0063] As noted above, the various described embodiments of impedance flow cytometry devices are applicable to the measurement of bacterial and microbial samples, such as AST. The embodiments of Figures 4-8 are particularly useful for this purpose compared to the embodiments of Figures 1-3, because they can handle small particles with sufficient measurement sensitivity to obtain meaningful data. Thus, the disclosed impedance flow cytometers and their use have applications for improved diagnosis of microbial infections and the formulation of antimicrobial agents. Furthermore, in the embodiments of Figures 4-8, the device flow channels can have dimensions significantly larger than typical bacterial cell sizes. Therefore, this type of device is useful for measuring samples of non-bacterial cells, which typically have sizes larger than bacterial cells, or mixed samples containing a range of particle sizes, and indeed, for measuring particles of non-biological origin.

[0064] Various exemplary measurement techniques and procedures that can be performed using impedance flow cytometry are now described. The description will be made with reference to devices such as the examples in Figures 4-8, but in general, these and similar methods may be performed using devices such as the examples in Figures 1-3.

[0065] The differential signal generated by an impedance flow cytometry device has a specific shape (the exact details of which depend on the order of the various electrodes, which can be selected to enhance the uniqueness of the signal shape or pattern). Therefore, at a simple level, the device can be used for particle or cell counting. Processing the differential signal can involve the simple identification and counting of all occurrences of a specific signal shape resulting from the passage of particles through the measurement region. This can be used for regular cell counting, but it can also be applied to identifying biological susceptibility to antimicrobial agents. Some antimicrobial agents act by destroying the structural integrity of microorganisms. As a result, if a strain of microorganism is susceptible to this type of antimicrobial agent, exposure of the sample to the antimicrobial agent will reduce the population of microorganisms in the sample over time. This can be identified by counting the number of treated microorganisms in a precisely volumetrically measured sample and comparing it to the count of an untreated sample of microorganisms at a specific time point or series of time points. This type of simple analysis may not require detailed calculation or analysis of the actual values ​​of the impedance of the particles in the fluid sample, may not require deriving an impedance signal from the differential signal, or may not require identifying the impedance values, properties, or characteristics of the particles from the impedance signal.

[0066] However, analysis of the impedance signal can reveal additional valuable information about cells, and in particular microbial susceptibility to antimicrobial agents. The disclosed method allows for a variety of impedance-based measurements to be performed in a simple and rapid manner with a minimal number of steps, which can reveal information about biological and non-biological particles, including cells and bacteria.

[0067] Different classes of antimicrobial agents have different modes of action and produce different biophysical changes in microorganisms. As mentioned above, some antimicrobial agents disrupt the structural integrity of microorganisms, thereby reducing population sizes that can be detected via particle counts in a precise sample volume. Other antimicrobial agents act by inhibiting cell wall synthesis, which can result in an overall increase in cell volume (size). The cell wall or cell membrane properties themselves may change (e.g., changes in thickness, electrical or material properties, or porosity), and the internal cell structure or composition may change. These various properties—cell size, cell wall / membrane properties, and internal properties—all contribute to the impedance profile or value of a cell. Therefore, measuring the impedance of particles in a sample can reveal cell characteristics. Comparing measurements of samples of microorganisms treated and untreated with an antimicrobial agent and identifying any differences can reveal whether a property changes with antimicrobial exposure, indicating measurable susceptibility to the antimicrobial agent. Measuring the impedance of particles in a sample can also reveal one or more properties, or the mode of action of an antimicrobial agent that causes a change in one or more properties. The antimicrobial agent can remain in the sample for cytometry measurement, or, if preferred, can be removed by washing before measurement. However, removal is not necessary, which is a beneficial aspect of the methods herein compared to optical cytometry techniques, which typically require the antimicrobial agent to be removed from the sample before adding the required dye. To determine susceptibility, a threshold level for the change in one or more properties reflected in the impedance measurement can be set. Susceptibility can be recognized when a comparison between the impedance signals from microbial samples not exposed to and exposed to the antimicrobial agent indicates that the amount of change is equal to or greater than the threshold. The threshold may be, for example, a threshold for the change in size of the measured property, or, for example, a threshold for the number of microorganisms in the sample that exhibit that change.

[0068] At a simple level, the magnitude of the differential signal obtained using the apparatus described herein, an example of which is shown in Figure 5(c), depends on particle size. Larger particles have a greater effect on or interact with the electric field in the flow channel, thus reducing current flow and resulting in a lower current being detected at the measurement electrodes. The differential signal will therefore contain peaks and troughs of larger amplitude than for smaller particles. Thus, a comparison of measurements from exposed and unexposed microorganisms may reveal antimicrobial susceptibility if the differential signal from the former measurement exhibits larger amplitude features than the latter sample. For this analysis, the differential signal can be considered directly, or the corresponding impedance value can be calculated from the differential signal.

[0069] When considering impedance values, recall that impedance includes two parts or components: a real part and an imaginary part, or more usefully, a magnitude |Z| and a phase θ. Any value or combination of these components can be analyzed to characterize particles in a sample fluid. Furthermore, the nature of the particle-electric field interaction depends on the frequency of the electric field. Therefore, measuring at different frequencies or two or more frequencies can yield different impedance results, which can reveal different particle characteristics. Measurements can be made by studying one sample of microorganisms at one frequency and another sample of the same microorganisms at a second frequency, by connecting different voltage or current sources to the signal electrode, or by configuring the signal source to output different frequencies to the signal electrode. However, more conveniently, the signal source used to drive the signal electrode can be configured to output two or more frequencies simultaneously. Appropriate filtering and / or processing of the differential signal or the impedance signal derived therefrom can be performed to separate different frequency components in the recorded measurements, thereby obtaining one or more impedance components (e.g., magnitude and / or phase) for each frequency component.

[0070] FIG. 9 shows a representation of the interaction of a particle (cell) with an electric field of different frequencies. A cell 42 suspended in an electrolyte solution is in an electric field (indicated by the dashed line) such as exists in the flow channel between the signal electrode and the measurement electrode. In FIG. 9(a), the frequency is low, meaning frequencies in the range of about 10 MHz or less, e.g., about 1 MHz or about 5 MHz. In this regime, the electric field passes around the cell 42 (note that the electric field lines do not penetrate the cell but are routed around it), and the measured impedance signal reflects the electrical volume of the cell (representing the physical size of the cell). Therefore, the cube root of the magnitude of the measured impedance, |Z| 1 / 3 , roughly reflects the electrical radius. In Figure 9(b), the frequency is high, which means a frequency higher than a low frequency, e.g., greater than about 10 MHz, e.g., about 40 MHz. In this regime, the electric field capacitively couples across the wall (membrane) of the cell 42 (note that the electric field lines pass through the cell relatively undisturbed). The effect is that the measured impedance signal reflects the electrical properties of the cell wall and / or membrane and / or the cytoplasmic properties of the cell's interior. This can be referred to as "electrical opacity." Thus, differences in these properties between two cells are evident as differences between the measured impedances at high frequencies. Note that useful values ​​for high and low frequencies will differ, or significantly differ, from these example values ​​for other cell types, other particle types, and / or different conductivities of the suspending electrolyte. For example, for non-bacterial cells in a suspending medium with a conductivity similar to physiological media, a high-frequency value of about 1 MHz may be appropriate, and for bacterial cells, a high-frequency value of about 10 MHz may be appropriate. Low frequencies are generally those at which the electric field does not penetrate particles, from which size information about the particles can be inferred. High frequencies are those above the selected low frequencies at which the electric field couples across the cell wall, allowing membrane- and wall-dependent properties of the cell to be probed. At much higher frequencies (above about 5 MHz for non-bacterial cells and above about 50 MHz for bacteria, considered within the high-frequency range of this disclosure), internal structure and component parts can be measured.

[0071] Thus, there is a distinction between measurements of the same particle at different frequencies (particularly between low and high frequencies as defined above) that depends on the particle's properties, and information about those properties can be inferred. Other parameters, including the conductivity and permittivity of the suspending electrolyte, also influence the distinction, but this and other parameters that are characteristic of the apparatus and test regime or protocol can be kept constant across multiple measurements and therefore do not affect the comparative analysis.

[0072] Measurements may be taken at only a single frequency, which may be a high frequency or a low frequency, or may be taken at two or more frequencies, typically two frequencies, either sequentially or simultaneously.

[0073] The two-frequency approach is to calculate, for each particle, the impedance at low frequency (magnitude, phase, real or imaginary components) and the impedance at high frequency. These values ​​are plotted on a graph along with values ​​for other particles in the same sample to generate a scatter plot. The magnitude of the low-frequency impedance, which indicates the electrical radius or electrical volume, can be plotted on the x-axis of the graph, and the magnitude of the high-frequency impedance can be plotted on the y-axis of the graph. Alternatively, the y-axis can plot the ratio of the high-frequency value to the low-frequency value, thereby normalizing the opacity to cell size, which is referred to as "electrical opacity."

[0074] In the figures presented herein, each point in the scatter plot (also called a scattergram) has a color that represents the number of particles, with black representing one particle and the point color becoming lighter gray as the number of particles increases. Thus, lighter colors indicate higher intensity (more particles) and darker colors indicate lower intensity (fewer particles).

[0075] Figure 10 shows four example scatter plots. Figure 10(a) shows measurements for a bacterial strain that was not treated with an antimicrobial agent. Measurements were taken at two frequencies: a low frequency of 5 MHz and a high frequency of 40 MHz. The impedance value of each cell at the low frequency, |Z| 5MHz is plotted on the x-axis, and the normalized impedance value of each cell at high frequency, |Z| 40MHz / |Z| 5MHz is plotted on the y-axis. Each data point corresponds to an individual particle in the sample. For calibration / reference purposes, the sample contained a fixed amount of plastic microbeads of known size and known dielectric properties (known impedance characteristics) that could be broadly comparable to bacterial size. The beads appear on the graph centered at a high frequency value of 1 and a low frequency value of 1.5 for single beads. Beads that adhere together in doublets and triplets appear as smaller clusters at higher low frequency values ​​to the right of the main bead population. However, all beads are well separated from the data points representing bacterial cells in the sample. These are centered at a high frequency value of approximately 0.75, spanning the low frequency range of approximately 1.6 to 2.4. A closed solid line is superimposed on the bacterial data points to indicate the location of the majority of the bacterial population. This solid line can be considered a contour, boundary, or gate and is useful for comparing measurements from different samples. This can be drawn to encompass all bacterial data points or a major percentage of the data points, such as 99%, 95%, 90%, 75%, or 50%, thus excluding outlying measurements. Known statistical techniques can be used to position and size the contour.

[0076] Figure 10(b) shows measurements for a sample of the same bacterial strain incubated for 30 minutes with an antimicrobial agent from the antimicrobial class known in this example as β-lactams. Because the antimicrobial agent does not affect the plastic material, the bead data points remain unchanged from Figure 10(a). However, the bacterial data show a significant shift to higher impedance values ​​at low frequencies, ranging from approximately 2.1 to 3, and a somewhat shift to lower impedance values ​​at high frequencies, centered around 0.7. The solid contour line in Figure 10(a) is shown in Figure 10(b). Few data points fall within the solid line, indicating that virtually the entire bacterial population has been substantially altered by the antimicrobial agent. A shift to larger low-frequency values ​​indicates an increased electrical radius, while a shift to smaller high-frequency values ​​indicates alterations to the internal cell structure and / or cell wall. Therefore, we infer that the antimicrobial agent has a measurable effect on the bacteria, and therefore that the bacteria are susceptible to that particular antimicrobial agent. Because β-lactam antimicrobial agents inhibit cell wall synthesis, they have the overall effect of increasing bacterial volume (size, diameter), as shown in Figure 10(b).

[0077] Figures 10(c) and 10(d) show two additional scatter plots for exposed and unexposed bacterial and plastic bead samples, where the bacteria are different strains than those in Figures 10(a) and 10(b). Figure 10(c) shows data for a bacterial sample not exposed to an antimicrobial agent. As previously mentioned, an outline has been drawn around the bacterial population. Figure 10(d) shows data for a bacterial sample after exposure to a β-lactam antimicrobial agent. Little difference from Figure 10(c) is observed, with nearly the entire bacterial population remaining within the outline. Therefore, we can infer that the antimicrobial agent had little, if any, measurable effect on the bacteria. We conclude that the tested strain is resistant to the antimicrobial agent at this particular concentration.

[0078] As noted above, other classes of antimicrobial agents have different effects on microorganisms. To determine whether a population of microorganisms is susceptible to a particular antimicrobial agent, any or all of three different parameters can be assessed from impedance measurements. Changes in cell size are indicated by changes in the response at lower frequencies (x-axis in Figures 10(a)-(d)), while changes in cell wall / internal properties are indicated by changes in the response at higher frequencies (y-axis in Figures 10(a)-(d)). A reduction in the total particle population resulting from damage to the cell structure by the antimicrobial agent to the point where they no longer register as particles is indicated by a decrease in the number of particles in the accurately measured volume. Each of these changes generates a fewer number of data points within the contour, as shown in Figures 10(a)-(d). This is because data points move outside the contour when cell size or wall / internal structure changes, or are removed when cell integrity is compromised. Therefore, a comparison of the number of data points within the same contour for exposed and unexposed microbial populations can be used to identify susceptibility. A metric representing susceptibility at a particular antimicrobial concentration can be defined as the number or percentage of microorganisms in the exposed sample that are inside the contour drawn for the unexposed sample. For example, in Figure 10(b), very few cells remain within the contour, and the metric is close to 0%, so the bacteria are susceptible to the antimicrobial at that concentration. In Figure 10(d), the majority of cells are inside the contour, and the metric is close to 100%, so the bacteria are resistant to the antimicrobial.

[0079] Figures 11(a) and (b) show some example scatter plots showing the susceptibility of bacteria to antimicrobial agents that destroy them, thereby reducing the total cell count. For each plot, similar to the graph in Figure 10, the electrical radius |Z of each cell at low frequency is plotted. 5MHz | 1 / 3 is plotted on the x-axis, and the normalized impedance value of each cell at high frequency |Z| 40MHz / |Z| 5MHzis plotted on the y-axis. Figure 11(a) shows impedance measurements from an unexposed sample containing a population of bacteria, with a contour or gate drawn to encompass most of the population, and a population of reference beads at a higher high-frequency response. Figure 11(b) shows impedance measurements from an exposed population. The x-y position of the data has not shifted significantly for the exposed bacteria, as there are few data points outside the contour, but the total cell count has decreased substantially, as indicated by the lower number of data points within the contour compared to the unexposed sample. Therefore, the bacteria are classified as susceptible to a particular antimicrobial agent.

[0080] The exemplary data thus far has been obtained using high and low frequencies for the signal applied to the signal electrode in the device. However, results can also be obtained by measuring at only one frequency. A scatter plot of the microbial population can then be generated by plotting the impedance magnitude against the impedance phase.

[0081] Figure 12 shows two additional example scatter plots of data obtained only at a high frequency of 40 MHz. The x-axis of each graph plots the electric radius (cube root of the impedance magnitude) measured at 40 MHz. The y-axis of each graph plots the phase of the impedance signal measured at 40 MHz. As previously mentioned, plastic microbeads were included in the sample, and these appear at a phase value of approximately 1. Data points with lower phase values, around 0.7, represent bacteria; therefore, the phase measurements can easily distinguish between bacteria and beads. Figure 12(a) shows a plot of a bacterial sample not treated with an antimicrobial agent. The electric radius measured for the population ranges from approximately 1.5 to 2.1. Figure 12(b) shows a plot of the same bacterial sample exposed to an antimicrobial agent. The bacterial population is shifted to higher x-axis values, covering a range of approximately 1.8 to 2.7. Because exposure to effective antimicrobial agents is known to alter bacterial cell size, we assume that the bacterial strain is susceptible to the applied antimicrobial agent.

[0082] In addition to the ability to easily distinguish a population of bacteria from a population of beads by looking at the phase value, it should be noted that phase can also be used to distinguish or identify the presence of different populations or subpopulations (groups or subgroups) of microorganisms within a single sample, where different microorganisms have different sizes and / or shapes and / or morphologies. The different microorganisms may be present in the sample initially, or may result from the effects of antimicrobial agents. For example, some agents alter cell size, effectively generating subpopulations of larger, smaller, and intermediate-persistent cells.

[0083] As a further alternative, the phase and magnitude values ​​of the impedance at different frequencies can be combined. Figure 13 shows additional exemplary scatter plots of data obtained at 5 MHz and 40 MHz. Similar to the graph in Figure 12, the graph in Figure 13 plots the phase at 40 MHz on the y-axis. However, the x-axis shows the electrical radius at the lower frequency of 5 MHz. Figure 13(a) shows measurements from a sample of bacteria untreated with an antimicrobial agent, while Figure 13(b) shows measurements from the same sample of bacteria treated with an antimicrobial agent to which the bacteria are susceptible. The bacteria and antimicrobial agent are the same as those in Figure 12. Both samples contained reference beads, which had phase values ​​near 1. Similar to the data in Figure 12, the bacteria are easily distinguished from the beads, having a lower phase value near 0.7. Note that the phase values ​​are the same as in Figure 12 because the phase data was obtained for the same high frequency. Again, as previously mentioned, the treated bacteria show a shift to larger values ​​of electrical radius, resulting from their susceptibility to the antimicrobial agent, which causes an increase in cell size. Note that in this example, the apparent increase in cell size is larger than in Figure 12, with values ​​ranging from approximately 2.1 to 3. This is due to the greater sensitivity of cell size to low-frequency measurements than to high-frequency measurements.

[0084] From these results, it can be seen that the method according to the present disclosure can be used to apply an electrical signal (voltage or current) to the first and second signal electrodes at one frequency or at two or more frequencies. Accordingly, the apparatus used to implement the method can include one or more electrical signal sources operable to generate one frequency or two or more frequencies. The one frequency can be a high frequency or a low frequency. The two or more frequencies can include two frequencies, one high and one low. The high frequency can be about 10 MHz or higher, for example, in the range of 10-1000 MHz, e.g., 40 MHz. In some applications, even higher frequencies, such as frequencies up to about 10 GHz, can be useful. The low frequency can be lower than the high frequency and be 10 MHz or lower, for example, in the range of 1-10 MHz, e.g., 5 MHz. However, other and / or additional frequencies are not excluded and can be selected with reference to the particular application. Similarly, the ratio of low to high frequencies can vary widely depending on the application.

[0085] As discussed above, e.g., with reference to Figures 10, 11, 12, and 13, a method according to the present disclosure can include obtaining a measurement from a sample of microorganisms exposed to a selected antimicrobial agent (where the microorganisms are particles suspended in an electrolyte to provide a fluid passing through an electrode arrangement as described herein to obtain a differential signal and, optionally, an impedance signal derived from the differential signal) and another measurement from a sample of the same microorganisms not exposed to the antimicrobial agent, and comparing the two measurements. The unexposed microbial population is used as a reference to which the exposed population is compared. A significant difference between the two measurements can indicate that the microorganisms are susceptible to the selected antimicrobial agent. The measurements can be arranged in a scatter plot of data points corresponding to individual microorganisms, and the difference can be assessed by referencing a contour line around the unexposed microbial population. A threshold can be set, for example, such that susceptibility is inferred if the antimicrobial exposure reduces the number or percentage of exposed microorganisms captured within the contour line below the threshold. To obtain two samples, a population of bacteria may be split in half before or after suspension in electrolyte; one half is incubated with an antimicrobial agent and the other half without, for a set time, e.g., 30 minutes. Reference plastic beads can then be added if necessary, and both samples are passed through an apparatus as described to obtain a differential signal from which impedance data can be derived.

[0086] However, it may be more useful to quantify antimicrobial susceptibility in more detail. In practice, susceptibility is more generally defined as whether a microbial strain is susceptible or resistant to a given concentration of an antimicrobial agent. While most antimicrobial agents overcome microorganisms at very high concentrations, such high concentrations may not be safely or practically achievable in the human body. Under this approach, a minimum inhibitory concentration (MIC) can be defined, which is the lowest concentration considered to have a significant inhibitory effect on a population of microbial strains. It can then be determined whether the MIC is achievable in the human body and, therefore, whether a particular antimicrobial agent can be used to combat infections caused by a particular microorganism. Therefore, it is useful to be able to measure the response of a microorganism to various concentrations of an antimicrobial agent in order to determine the MIC. Due to its simplicity, the method disclosed herein is well suited to enabling this determination.

[0087] The method described above can be expanded by dividing a microbial sample into three or more groups and exposing each group, including an unexposed group that serves as a reference sample, to a different concentration of antimicrobial agent, as described above. In this way, the MIC can be determined, or a previously established value for the MIC can be verified or retested. To assess the MIC, similar concentrations of groups or populations of microorganisms are incubated with various antimicrobial concentrations (usually a control or reference concentration of 0, a concentration considered to be the clinically relevant MIC, and two or more concentrations (or dilutions) on either side of the MIC). Thus, the microbial sample is divided into six groups, each of which undergoes impedance measurements.

[0088] As an example, microbial sampling for performing MIC assessment may involve picking a colony of the microorganism from a plate and incubating the colony overnight in an appropriate medium, such as trypticase soy broth (TSB), to generate a culture. The culture may then be grown in Mueller-Hinton broth (MHB) at a concentration of 5 x 10 5The culture is diluted to 1000 cells / mL and incubated at 37°C for 30 minutes to obtain an actively dividing culture. An aliquot (950 μL) of this actively dividing culture is added to each of seven pre-warmed test tubes, each containing 50 μL of MHB and a dose of an antibacterial agent, such as the antibiotic meropenem, to obtain a set of final antibacterial concentrations of 0, 0.25, 0.5, 1, 2, 4, and 8 mg / L. The tubes are incubated for 30 minutes (antibiotic exposure), then washed once in Hank's Balanced Salt Solution (HBSS), followed by a 1:10 dilution in HBSS. Reference beads of 1.5 μm diameter are added to each sample (10 4 / mL), and then impedance flow cytometry measurements can be performed as described above, for example, by introducing the sample into the cytometer device using a syringe at a rate of 30 μL / min for 3 minutes.

[0089] Figure 14 shows six scatter plots of impedance measurements of six groups of bacteria exposed to a series of six antimicrobial concentrations. In this example, the concentrations are 0 μg / mL (control), and 0.5, 1, 2, 4, and 8 μg / mL, as shown on the graph, with 2 μg / mL being the known, predetermined MIC of the antimicrobial for the bacteria being tested. Figure 14(a) shows the control or reference group not exposed to the antimicrobial, and a gate contour is drawn around the bacterial population to encompass the majority of data points. For lower antimicrobial concentrations (Figures 14(b)-(d)), the bacteria can be seen to be resistant, as no data points fall outside the contour. Only at concentrations of 4 μg / mL and 8 μg / mL is there a significant shift from the contour observed (Figures 14(e) and (f)). For these measurements, data were obtained at two frequencies: a low frequency of 5 MHz and a high frequency of 40 MHz. The impedance values ​​|Z| for each cell at low frequency were plotted. 5MHz is plotted on the x-axis, and the normalized impedance value of each cell at high frequency |Z| 40MHz / |Z| 5MHz is plotted on the y-axis.

[0090] As discussed, the measured "shift" in biophysical properties resulting from exposure to an antimicrobial agent to which a microbial strain lacks resistance is identifiable as a change in cell number within the contour marking the distribution of impedance measurements from the unexposed population, and can be quantified in many different ways, including a change in cell size, a change in cell wall / membrane properties, and / or a decrease in cell number, or a combination of these.

[0091] Figure 15 shows graphs summarizing measurements of these properties for 10 different bacterial strains after exposure to different antimicrobial concentrations, with the values ​​of the various properties determined from impedance measurements obtained by the method disclosed herein. Figure 15(a) shows the total cell number (y-axis) normalized to the reference cell number versus the antimicrobial concentration (x-axis). Figure 15(b) shows the cell number within the contour gate (y-axis) normalized to the reference number versus the antimicrobial concentration (x-axis) (thus similar to the total cell number in Figure 15(a)). Figure 15(c) shows the cell size (y-axis) normalized to the reference cell size versus the antimicrobial concentration (x-axis). Figure 15(d) shows the opacity (y-axis) normalized to the reference opacity versus the antimicrobial concentration (x-axis). The group in line A corresponds to bacteria known to be highly resistant to antimicrobials; therefore, the properties are not significantly affected, even at higher concentrations, with the lines remaining largely horizontal. The group labeled line B represents strains with moderate resistance; therefore, the characteristics change only at higher concentrations, and the line deviates from the horizontal plane at higher concentrations. The group labeled line C represents strains known to be highly susceptible to antimicrobials; therefore, the characteristics change even at very low concentrations, and the line deviates from the horizontal plane as soon as the concentration exceeds zero. These four different graphs can be used separately or together to make a quantitative determination of bacterial susceptibility. As an example, the total bacterial count for group C in Figure 15(a) is lower at 0.25 μg / ml (therefore, the bacteria are susceptible at this concentration), while the line for group B only shows a decrease in cell count at 4 μg / ml. A similar trend can be observed for cell size, as shown in Figure 15(c). A threshold can be defined to determine the appropriate MIC. For example, an antimicrobial may require that cell size increase by 110% or more to be considered effective; the concentration that produces this change is considered the MIC. Different antimicrobials and different microorganisms have different profiles, resulting in different thresholds for various attributes to quantify susceptibility and make a determination of susceptibility or resistance for each isolate / antimicrobial concentration. Data can be analyzed / correlated and / or calibrated against standard techniques for measuring susceptibility.

[0092] A drawback of optical cytometry techniques is that antimicrobial agents must often be removed from samples by a washing step before adding the required dye. This is because the dye can interfere with microbial growth. Therefore, the sample only captures the antimicrobial effect at the time of washing, and the optical measurement provides only a "snapshot." This prevents studying the evolving effect of antimicrobial agents over time without preparing multiple washed samples after different incubation times, which is inconvenient and expensive due to the expensive nature of the dye. This latter point makes assessing MICs via optical cytometry expensive due to the need for multiple samples at different antimicrobial concentrations.

[0093] The impedance flow cytometry method described herein addresses this issue by enabling continuous impedance measurements from a single microbial sample, thereby enabling the evolution of an agent's antimicrobial effect to be assessed. To accomplish this, a single microbial population is prepared in an electrolyte solution, such as growth medium, as the fluid passed through the impedance measurement device described above. An antimicrobial agent is applied to the microorganisms and allowed to remain in the sample. The fluid containing the microorganisms and the antimicrobial agent is rapidly passed through the device flow channel so that the first impedance measurement can be recorded immediately after the antimicrobial agent is added, e.g., within the first minute. Over this time scale, the antimicrobial agent may have no measurable effect on the microorganisms; therefore, the microorganisms can be considered unexposed to the antimicrobial agent, and this first measurement can serve as a reference measurement corresponding to measurements from an unexposed microbial sample. Passage of the fluid through the flow channel is maintained at a constant rate, either by continuous extraction from a larger sample or by recirculation of the fluid from a smaller sample, and multiple measurements are taken, each at a specific time interval, e.g., one minute after the first reference measurement. Alternatively, measurements may be taken continuously, with results divided into data collected in successive time periods or bins, such as one-minute intervals. The antimicrobial agent continues to act on the microorganisms throughout the entire measurement period, and its effect over time can be determined by comparing different measurements. The portion of the sample corresponding to each time interval can be considered a subsample, and an impedance measurement is collected for each subsample. In some cases, for example, if the antimicrobial agent acts rapidly on the microorganisms, it may be desirable to add the antimicrobial agent to the sample after measurements on that sample have begun. This allows the first measurement to serve as a reference measurement from unexposed microorganisms. To accomplish this, a single population of microorganisms can be prepared in an electrolyte solution, such as growth medium, to obtain a fluid that is passed through the impedance measurement device described above. One or more measurements are taken, and then the antimicrobial agent is added to the fluid. Measurements then continue on the exposed sample as described above.

[0094] Figure 16 shows a sequence of scatter plots of data acquired in this manner using a high frequency of 40 MHz and a low frequency of 5 MHz to obtain impedance measurements. A bacterial population was exposed to an antimicrobial agent and continuously measured over a 26-minute period. The resulting impedance data was separated into bins corresponding to 1-minute intervals and plotted on a graph. As in the previous example, the sample fluid contained plastic microbeads, which appear as a cluster in the upper left corner of each graph. The upper left plot shows data collected during the first minute (times 0 to 1 minute), designated as the reference or control data for unexposed bacteria. A contour line or gate was drawn around the unexposed bacterial population on this graph and then replicated in each subsequent graph, allowing for the identification of changes in the bacteria over time. Examination of the sequence of graphs reveals that after approximately 15 minutes, the bacterial population begins to deviate significantly from the contour line. Therefore, we can infer that the bacteria are susceptible to a particular antimicrobial agent. After 26 minutes, nearly the entire population deviates from the contour line. The shift is towards higher low frequency values, which indicates an increase in cell size, and towards lower high frequency values, which indicates that the antimicrobial agent also changes the properties of the bacterial cell wall or its internal structure.

[0095] 17 shows a further exemplary device having an alternative arrangement of electrodes. As in some previous examples, eight electrodes are provided to define four current paths in two groups, each comprising a first current path and a second current path. However, whereas the previous examples included only one current path orientation within a single system, the example of FIG. 17 includes two orientations of the current paths, which allows additional information to be determined about particles in a sample.

[0096] In particular, the device is configured such that, in each of the first electrode group 50 and the second electrode group 52, there is a current path substantially transverse to the direction of fluid flow and a current path substantially parallel to the direction of fluid flow. In the first electrode group 50, a first signal electrode 60a supplied with +V from a voltage source 70 is positioned above the channel opposite a first measurement electrode 62a below the channel to define a first current path transverse to the direction of fluid flow, from which a current I4 is measured. A second signal electrode 64a supplied with −V from a voltage source 72 is positioned below the channel adjacent to a second measurement electrode 66a, also below the channel, to define a second current path parallel to the direction of fluid flow, from which a current I3 is measured. As previously described, I3 and I4 are combined to generate a first summed signal I5 from the first electrode group 50. Similarly, in the second electrode group 52, the first further signal electrode 60b faces the first further measurement electrode 62b to define a first transverse current path 16, and the second further signal electrode 64b is adjacent to the second further measurement electrode 66b to define a second parallel current path 17. I6 and I7 are combined to generate a second summed signal 18, which, as in the previous embodiment, is processed by the current-to-voltage converters 34a, 34b and the differential amplifier 36 to determine a differential signal.

[0097] By providing differently oriented current paths along the same flow channel, information about particle shape can be revealed. In the absence of any particles, the magnitudes of the various current paths are approximately equal and sum to approximately zero, as previously described. In the presence of spherical or nearly spherical particles, the impedance signal measured for the transverse current path has approximately the same magnitude as the impedance signal measured for the parallel current path, as described with respect to Figures 1-9. However, if the particle 42a is non-spherical, such as an elongated, rod-shaped bacterium (e.g., a bacillus), it will interact with the two current path directions in different amounts, resulting in signals of different sizes. If an elongated particle is oriented with its longest axis aligned with the channel flow direction, it will generate a larger change in the transverse current path than in the parallel current path. Thus, the summed signals derived from the two current paths within an electrode group will be different for elongated particles compared to spherical particles, and the difference is related to the degree to which the particle shape differs from a sphere (i.e., its eccentricity or elongation). Therefore, obtaining a sum signal from two differently oriented current paths (such as a transverse and a parallel path) provides a differential signal that can reveal information about particle eccentricity or shape. This is useful for distinguishing different types of bacteria, such as bacilli (rods) and cocci (spheres), or for identifying bacterial chains. Furthermore, it can be used to enhance AST measurements by identifying particles arrested during the division cycle, as in the case of treatment with β-lactam antibacterial agents. For example, treatment of cells with different concentrations of β-lactam antibacterial agents is known to result in different and distinct morphological forms. Antibacterial agents that act at the initial blocking point result in dumbbell-shaped cells, while those that act at a later time result in lemon-shaped cells. (MJ Pucci et al., Bacteriology 165 682-688, 1986).

[0098] The particle geometry can reveal other characteristics. For example, if the flow of sample fluid through a cytometer channel creates sufficient shear stress, cells can be deformed or crushed as they move along the channel. Softer cells are more deformed and acquire a greater degree of eccentricity than stiffer cells. Therefore, configurations such as the example in FIG. 17, which use differently oriented current paths to detect cell eccentricity, can further be used to distinguish or determine particle mechanical properties. Softer particles generate different sum and differential signals than stiffer particles due to their different flow-induced shapes. The action of antimicrobial agents on microbial species can also result in changes in mechanical properties.

[0099] Note that the electrodes may be arranged to provide two orientations of the current path along the flow direction in a different order than that shown in FIG.

[0100] Figure 18 shows a scatter plot of impedance data obtained from two different cell types. As previously mentioned, each data point represents a single particle in the sample. The vertical axis represents a "deformability" measure, obtained by dividing the impedance measurements from one or more parallel current paths by the impedance measurements from one or more transverse current paths. The horizontal axis represents the particle's electrical diameter, obtained by averaging the impedance signals from the two measurement directions, which approximates cell size. Alternatively, the diameter can be obtained along the electrical radius measurements discussed in relation to Figure 12. Measurements were obtained for two groups of spherical B3Z cells. One group was modified by fixation with glutaraldehyde to increase membrane stiffness. Note that measurements can be performed on a single sample containing both groups of cells, or on two samples, each containing one group. Thus, the two groups of cells have different mechanical properties and appear on the scatter plot as two well-separated populations. Measurements of a reference population of 7 μm beads are also shown. The more firmly anchored cells remain substantially spherical in the fluid flow along the channel, and therefore the impedance signals measured for the two orthogonal current paths are similar. Therefore, the deformability of these cells is measured as close to 1 arbitrary unit. In contrast, untethered cells are deformed by the flow and elongate along the channel direction. Therefore, the impedance signal measured along the channel direction is reduced compared to measurements across the channel, and the deformability measurements are reduced to less than 1 AU. In this example, it is measured at approximately 0.5 AU. In this way, the mechanical properties of individual cells and cell populations can be identified, and different cell populations can be distinguished from each other.

[0101] A technique for assessing antimicrobial susceptibility by determining the minimum inhibitory concentration (MIC) is described above, along with instructions on how to do this using the described impedance flow cytometry method. An alternative technique is breakpoint analysis, in which a bacterial sample is exposed to one or two concentrations of an antimicrobial agent (antibiotic) and classified as susceptible / nonsusceptible (S / NS), resistant / nonresistant (R / NR), or intermediate resistance depending on the sample's response to the antimicrobial agent. Responses can be measured using the described impedance flow cytometry.

[0102] In breakpoint analysis, bacteria are evaluated at one or two predefined concentrations of an antibiotic, as tabulated by standards organizations such as the Clinical & Laboratory Standards Institute (CLSI) in the United States and the European Committee on Antimicrobial Susceptibility Testing (EUCAST). To perform the analysis, bacterial growth is evaluated at a first concentration, X, which defines the S / NS boundary. If bacteria do not grow (i.e., the number of bacteria in the test sample does not increase), they are classified as susceptible to the antibiotic. If bacteria grow, they are classified as not susceptible to the antibiotic. Furthermore, bacterial growth can be evaluated at a second concentration, Y, which is higher than concentration X and defines the R / NR boundary. If bacteria grow, they are classified as resistant to the antibiotic; if bacteria do not grow, they are classified as not resistant. The values ​​of concentration X and concentration Y depend on the bacterial strain and the type of antibiotic. Some strains of bacteria may grow at concentration X (or higher) but not at concentration Y; these are classified as not resistant but not susceptible, a characteristic commonly referred to as intermediate resistance. For some antibiotics and some bacterial species, there is no intermediate range; in other words, concentrations X and Y are equivalent, and testing at only one concentration is necessary. In either case, a sample of bacteria not exposed to antibiotic is also tested using impedance flow cytometry to obtain the reference population gate or contour described above.

[0103] As a non-limiting example, samples for impedance flow cytometry-based breakpoint analysis can be prepared in the following manner: Three colonies of bacteria are selected from a plate and added to 3 mL of MHB. The sample is vortexed to resuspend the bacteria in broth, and then 5 x 10 cells are added to the MHB. 5 The samples are then diluted to a concentration of 1000 cells / mL. The samples are then incubated for 30 minutes to obtain actively dividing cultures. A 500 μL aliquot is added to a test tube containing 500 μL of preheated MHB, each with a final antibiotic concentration at the clinical breakpoint (S / NS and / or R / NR), e.g., according to current EUCAST guidelines. These can be 2 mg / L (S / NS) and 16 mg / L (R / NR) for the antibiotic meropenem, 1 mg / L for ciprofloxacin, 8 mg / L for gentamicin, 4 mg / L for colistin, or 8 mg / L for ceftazidime, amoxicillin / clavulanate, and cefoxitin, along with a 0 mg / L control sample. After incubating each tube for 30 minutes (antibiotic exposure), the sample is diluted 1:10 in HBSS and 1.5 μm reference beads are added. The sample can then be passed through the impedance flow cytometry device at a rate of 30 μL / min over a 2 minute measurement period.

[0104] Figure 19 shows bar graphs of exemplary data measured using impedance flow cytometry to perform breakpoint analysis. Eleven different bacterial strains were exposed to the antibiotic meropenem. For each strain, the chart shows the percentage of the bacterial population remaining within a reference gate or contour (measured on an unexposed sample of bacteria) after exposure to the antibiotic. Figure 19(a) shows the susceptible / non-susceptible (S / NS) breakpoint data, where the antibiotic concentration is 2 mg / L. Figure 19(b) shows the resistant / non-resistant (R / NR) breakpoint data, where the antibiotic concentration is 16 mg / L. Bacteria are labeled as KP (Klebsiella pneumonia), EC (Escherichia coli), ACB (Acinetobacter baumannii), and PAE (Pseudomonas aeruginosa). Bar graphs show mean values ​​± standard deviation (N = 3; * p<0.05; ** p<0.01; *** p<0.001, p-value obtained using an independent-samples Student's t-test (one-tailed). Bar shading represents susceptible and resistant strains as determined by conventional broth microdilution techniques, with darker bars representing resistant strains and lighter bars representing susceptible strains. There was good agreement between these designations and the measured percentage of cells within the control gate, demonstrating that impedance flow cytometry is an accurate technique for performing breakpoint analysis. The medium-shaded bar in each graph is for KP(CNCR), a carbapenemase-negative strain of KP that is resistant to carbapenems.

[0105] Figure 20 shows a set of scatter plots of data obtained using impedance flow cytometry for resistant and susceptible strains of three bacteria, Klebsiella pneumoniae (KP), Escherichia coli (EC), and Staphylococcus aureus (SA), exposed to different antibiotics, as indicated in the plot header. Various antibiotics have different mechanisms of action that alter cell size, shape, structure, and / or number, resulting in different impedance responses that can be detected by impedance flow cytometry. This can be seen from the different behavior of the data points representing cell populations relative to the gate contour. Resistant bacteria are not affected by the antibiotic, so the population remains roughly within the gate contour. Susceptible bacteria are affected by the antibiotic, so the population changes with respect to the size, shape, and location of the gate contour. Antibiotic concentrations were the R / NR breakpoint concentrations for the various bacterial strain / antibiotic combinations.

[0106] Scatter plots for the antibiotics colistin, gentamicin, ciprofloxacin, ceftazidime, and Co-amoxiclav are shown as electrical cell size or radius (which is the cube root of the measured low-frequency (5 MHz) impedance, as explained above) versus electrical opacity (which is the measured high-frequency (40 MHz) impedance normalized to the low-frequency impedance, as explained above). The scatter plot for cefoxitin is shown as electrical cell size versus the measured high-frequency (40 MHz) phase impedance, as this measure provides a clearer distinction between resistance and susceptibility to the specific antibiotic mechanism of cefoxitin.

[0107] Figure 20 also includes a bar graph similar to that of Figure 19 showing the percentage of cells remaining within the gate outline for each bacteria / antibiotic combination. Again, darker and lighter shading corresponds to resistance and susceptibility, respectively, as determined by conventional broth microdilution, demonstrating that comparable results can be obtained using impedance flow cytometry.

[0108] With particular regard to phage susceptibility, there are many molecular events that occur during phage infection that are evident from impedance cytometry data and are important considerations when determining whether a bacterial isolate is susceptible to any given phage. These molecular events include, but are not limited to, the initial binding of the phage to the cell (e.g., a change in opacity), loosening of the bacterial outer membrane and peptidoglycan layer due to the effects of phage depolymerase, either alone or in combination with phage lysin (e.g., a change in opacity; a change in electrical radius), replication and production of progeny phage within the bacterial cell (e.g., an increase in electrical radius as the bacterium swells), the effect of phage holin, which results in selective permeabilization of the cytoplasmic membrane and disruption of proton motif forces (e.g., a change in opacity), cell lysis and rupture mediated by phage lysin (e.g., a change in opacity; a decrease in the total number of impedance signals), and inhibition of growth (e.g., a decrease in the cell impedance signal compared to an uninfected control sample or reference). One or more of these events can be examined using the methods of the present invention. Each molecular event can result in a change in one or more properties, including opacity, electrical volume, electrical radius, and total impedance signal. Importantly, many of these events are not evident from other optical / fluorescence flow cytometry methods, which cannot assess the direct impact of phages or other antimicrobial agents on bacterial membranes. While these important events are not part of the output of prior art methods that clinicians or other physicians can use to make decisions about the suitability of a particular phage or phage cocktail for treatment, the method of the present invention can provide evidence for this. Because bacterial impedance flow cytometry methods look at physical events in single bacteria, they also provide information that is not evident with other electrical impedance techniques that measure changes in the medium due to bacterial metabolism. This allows both a more rapid assessment of susceptibility to phages and a more detailed analysis that can serve as the basis for selecting specific phages for treatment. Importantly, this includes the low frequency of phage-resistant bacterial cells in a population, which may be inherently present in the population (often referred to as heteroresistance) or may emerge over time due to selective pressure.Being able to observe changes at the level of individual bacteria is highly preferable to measuring metabolic changes representative of an entire population, which may be relatively insensitive to low-frequency changes.

[0109] Similarly, with regard to antimicrobial peptides, numerous events can be observed using impedance flow cytometry methods. These include, but are not limited to, binding to cells (e.g., a change in opacity), disruption of the LPS layer, outer membrane, or peptidoglycan (e.g., a change in opacity), permeabilization of the inner membrane resulting in either leakage or dissipation of proton motive force (e.g., a change in opacity; loss of impedance signal relative to a control), and cell lysis (e.g., a decrease in the number of cellular impedance signals relative to a total or control), and inhibition of growth (e.g., a decrease in the number of impedance signals relative to an untreated control or reference). One or more of these events can be investigated using the methods of the present invention. Each molecular event can result in a change in one or more properties, including opacity, electrical volume, electrical radius, and total number of impedance signals. Similar considerations are relevant for monitoring antimicrobial peptide activity using bacterial impedance flow cytometry compared to other methods, as discussed above. Importantly, many of these events are not evident from other optical / fluorescence flow cytometry methods, which cannot assess the direct impact of antimicrobial peptides on bacterial membranes. This allows both a more rapid assessment of susceptibility to antimicrobial peptides and a more detailed analysis on which to base the selection of specific antimicrobial peptides for treatment. Importantly, this includes being able to identify the low frequency of resistant bacterial cells in a population.

[0110] The impedance flow cytometry method according to the examples and embodiments herein offers many advantages. Tests and measurements can be performed quickly and with improved sensitivity, particularly for smaller particles such as bacteria, making the method useful for AST and other microbial assays. Suitable devices for implementing the method, such as chip-based formats suitable for mass production, are compact, potentially portable, inexpensive, and scalable for multiple simultaneous tests. In the context of testing the susceptibility of microorganisms to antimicrobial agents, testing can be rapid, simple, and inexpensive, as no dyes or other labeling media are required. This also allows for continuous monitoring of the response of any given sample to antimicrobial agents over extended periods of time, which is typically not possible with dye-based testing procedures such as optical cytometry.

[0111] As an example of the improved testing speed offered by impedance flow cytometry, consider the case of a patient in an intensive care unit who presents with a urinary tract infection and is immediately prescribed the antibiotic co-amoxiclav, the traditional standard of care for this condition. The patient sample is sent for testing within the hospital microbiology unit, and after overnight bacterial culture, which takes approximately 16 hours from sample collection, the isolate is identified as Escherichia coli (E. coli) using, for example, a Bruker Biotyper system, which takes another 2 hours or so. This identification may result in a change of antibiotic to a type deemed more appropriate, followed by a further period of approximately one day during which patient observation indicates whether the bacteria is resistant to the antibiotic and further antibiotic changes may be necessary. In contrast, a rapid AST using an impedance flow cytometer performed at the 16-hour mark using one or more antibiotic types can identify the antibiotic to which the bacteria is susceptible in just a 30-minute period, thereby optimizing the prescription. For example, an E. coli strain may be found to be resistant to co-amoxiclav but susceptible to meropenem.

[0112] The methods described herein can be used to measure and analyze particles of non-biological origin, and therefore examples can be considered more generally as particle impedance measurement methods, which can be performed using devices configured (e.g., with respect to their dimensions) for use with biological particles (particularly cells, which may or may not be bacterial) or non-biological particles, or any particle type. The terms "impedance flow cytometry," "impedance flow cytometry method," "impedance flow cytometer," and "impedance flow cytometry device" are intended to cover any of the methods and devices described herein, regardless of the nature of the particles, although in some examples particle types are relevant, such as impedance flow cytometry for AST and MIC determination. The present disclosure is not limited in this respect.

[0113] Impedance flow cytometry can be used to measure the electrical (impedance) properties of bacteria without dyes. This technique allows for direct measurement of the organism's phenotypic response and does not require incubation with dyes. Furthermore, this technique can be implemented on a compact and scalable device, allowing for several measurements to be performed in parallel using custom-designed chips with multiple channels. Electrical properties can be measured continuously as a function of time to determine the evolution of the response to antimicrobial agents. This is not typically done using dyes, as the dye is washed out before measurement.

[0114] Prophylactic phage therapy for improved prevention or control of bacteria causing chronic disease Phage therapy can be used to prevent or control microorganisms that cause chronic disease. Phage therapy has the advantage that specific organisms can be targeted with reduced interference with the microbiome because the phages target specific species. Bacterial impedance flow cytometry can be used to identify phages to which microorganisms that contribute to specific chronic conditions are susceptible. The following microorganisms associated with acute and chronic conditions are possible targets for which appropriate phage therapy can be identified using the methods described herein:

[0115] B. fragilis strains harbor genetic elements encoding a metalloprotease enterotoxin designated Bacteroides fragilis toxin, or BFT. Toxin-carrying strains, enterotoxigenic B. fragilis (ETBF), cause acute and chronic enteric disease in children and adults. 5,6 .

[0116] The exotoxin-secreting enterobacterium Enterococcus faecalis is a potential risk factor for alcoholic hepatitis. 7 is an important contributing factor.

[0117] Studies by various authors have linked the presence of colibactin-producing Enterobacteriaceae with colorectal cancer. 8~10 Phages have been proposed to be involved in the prevention and / or treatment of colorectal cancer. 16~18 .

[0118] Fusobacterium nucleatum is a bacterium that causes 11 Ulcerative colitis, colon cancer 12 The occurrence of cancer and various forms of cancer treatment 13 The phage has been associated with treatment failure in F. nucleatum. 14 It has been isolated for its biofilm 15has been shown to destroy

[0119] K. oxytoca is a normal inhabitant of the human intestinal tract, but in some patients taking penicillin, the proliferation of this pathogenic commensal organism can lead to antibiotic-associated hemorrhagic colitis (AAHC), the causative agent of which is penicillin. 1 It is a PBD derivative called

[0120] and / or humans with genes related to choline and carnitine metabolism 2~4 Individual strains of various species of gammaproteobacteria (e.g., Acinetobacter baumannii, Klebsiella pneumoniae, Proteus mirabilis, Providencia spp., Citrobacter spp.) produce trimethylamine, which is associated with cardiovascular disease in humans.

[0121] Pseudomonas aeruginosa, Stenotrophomonas maltophilia, Burkholderia cepacia, Burkholderia cenocepacia, Burkholderia multivorans, Achromobacter spp., Pandoraea spp., and Ralstonia spp. are all associated with chronic infection / long-term colonization in patients with cystic fibrosis. [Example]

[0122] Example 1: Assessment of phage susceptibility using bacterial impedance flow cytometry (BIC); single phage preparations 1.1 Method for determining bacterial impedance flow cytometry profiles The protocol uses bacteria from clinical samples plated, for example, on TSA or selective plates and grown overnight at 37°C. Preferably, plates are freshly cultured before use. Three colonies are picked from the plate, inoculated into 3 mL of broth, and incubated at 37°C for 30 minutes with shaking. To normalize the number of bacteria used in the experiment, the grown culture can be compared to McFarland Standards. Preferably, cell counts are performed on a bacterial impedance flow cytometry platform by diluting 200 μL of culture in 790 μL of PBS + 10 μL of size standard bead stock (1 μL of bead stock diluted in 1 mL of PBS). The number of cells in a 15 μL sample was calculated using the bacterial impedance flow cytometry "cell count" function in the script "ImpedanceGUI_V1." This allows for the calculation of the number of colony-forming units (CFU) per ml. Bacteria are counted at 5.5 x 10 5 Dilute to a starting concentration of 10 CFU / mL. Bacteria were diluted into 12 mL aliquots and then separated into 4 x 3 mL aliquots for assessment of phage susceptibility.

[0123] Phage preparations were prepared using standard methods, and stocks were filtered through 0.2 μm filters and / or partially purified using PEG precipitation from bacterial culture supernatants. Phage were titrated using standard microbiological methods described in Example 2 and maintained as working stocks at 4°C. An appropriate concentration of phage was added to the bacterial suspension so that there was an excess of phage over bacteria. Typically, phage was added at a multiplicity of infection (multiplicity of infection) of 10-100 (multiplicity of infection: phage to bacteria). Cultures containing phage and bacteria were incubated at 37°C in a static incubator for up to 90 minutes before analysis.

[0124] At the end of the incubation, samples are analyzed by bacterial impedance flow cytometry.

[0125] [Table 1]

[0126] [Table 2]

[0127] 1.2 Data analysis and interpretation. The data obtained by this method show clear differences in the susceptibility profiles of individual phage / bacteria combinations, as shown in Figures 21-24.

[0128] Figure 21 shows the time course of bacterial impedance flow cytometry profiles for A. baumannii susceptible (NCTC 13302) and B. nonsusceptible (NCTC 10303) strains treated with phage Ab_2. The scatter plot shows the distribution of impedance measured for individual bacteria at 15 minutes (T15) and 90 minutes (T90). Standard methods were followed, except a low multiplicity of infection (MoI 0.1; 1 phage per 10 bacteria) was used. The spread in electrical radius measurements increases in susceptible samples. The mean and mode electrical radii of susceptible samples also increased. Threshold tests, including the spread of electrical radius results or the average radius for a cohort of measurements centered around a particular phase, e.g., 0.5, or at a particular phase, can distinguish between susceptible strains, e.g., A. baumannii (NCTC 13302), and non-susceptible strains, e.g., A. baumannii (NCTC 10303). Bacterial impedance cytometry profiles have a different phase and opacity than, for example, microbeads. This can be used to distinguish other components, e.g., microbeads, from bacterial profiles with known phases.

[0129] Figure 22 presents a bar graph of the analysis of the data presented in Figure 21. Analysis of the data presented in Figure 21 demonstrates a significant reduction in total cell number (A), expressed as a percentage increase relative to the cell number at 15 minutes, in the susceptible strain (shown on the right, hatched at each time point) compared to the resistant strain (shown on the left, without hatching at each time point). A slight residual increase in the susceptible population was observed at 90 minutes of incubation, reflecting a scenario in which not all bacteria in the population were infected with phage, consistent with the low MoI (0.1) used in this experiment. The data were further analyzed to show the percentage of cells located within a contour enclosing 95% of the normal, untreated bacterial population (B). This further indicates the displacement of surviving bacteria from the contour with the susceptible strain, reflecting an increase in the electrical radius of the cells (indicating an increase in bacterial cell volume). This was not observed with the resistant strain of A. baumannii; the number of cells gated within the contour continued to increase rapidly over the time course, and no significant number of cells with increased volume was observed.

[0130] Figure 23 shows bacterial impedance flow cytometry profiles obtained in an experiment conducted to evaluate the effect of treating a population of a susceptible strain of A. baumannii NCTC 13302 with a high phage concentration (MoI = 10 over a time course from 0 (T0) to 60 minutes (T60)). Figure 23A shows the bacterial impedance flow cytometry profile obtained from a sample of the susceptible strain after treatment with a high phage concentration. Figure 23B shows the bacterial impedance flow cytometry profile obtained from a sample of the same susceptible strain that was not treated with phage.

[0131] Figure 24 shows an analysis of the data shown in Figure 23A from infection of NCTC 13302 with phage Ab_2 at an MoI of 10. The data show a decrease in total viable counts (A) and rapid migration of phage-treated bacteria from the outlined area within 30 minutes (B) (shown on the left hand side of the figure with hatching at each time point), indicating increased cell size, compared to untreated control cultures (shown on the right hand side of the figure with no hatching at each time point), both incubated for the same time.

[0132] The data show that phage infection of susceptible strains, alone or in combination with a decrease in the number of cells within a contour defined by the 95th percentile of the control population, is associated with a decrease in viable bacterial count. This control population can be defined based on a control culture incubated in parallel with the phage-treated population or by using a TO sample of the phage-treated sample as a control. Migration from the contour area indicates a shift on the x-axis indicating an increase in the cell's electrical radius, which is an indirect measure of cell volume. This migration pattern, seen only in susceptible bacteria, is due to intracellular phage proliferation, ultimately leading to its rupture and release of phage progeny. This phenotype is observed within 15 minutes of phage addition at a high MoI in susceptible cells, which may be sufficient to identify the susceptibility of clinical isolates. This allows, for example, bacterial impedance flow cytometry-based phage susceptibility tests to reach results in 15 to 120 minutes for rapidly growing bacterial species. For slow or very slow-growing bacteria, such as Mycobacterium, the time required for susceptibility measurements may need to be extended to 4 or 8 hours.

[0133] 1.3 Creation of bacterial strain susceptibility matrices using individual phage stocks. To validate the utility of bacterial impedance flow cytometry testing for rapidly assessing the susceptibility of bacterial isolates to phages, we conducted a study to validate a matrix approach to inform potential phage treatment. Four drug-resistant isolates of Acinetobacter baumannii and Pseudomonas aeruginosa, and in some cases multidrug-resistant isolates, were incubated with each of three phage preparations according to the standard protocol described above, and susceptibility was measured by bacterial impedance flow cytometry. The matrix below shows the susceptibility of different isolates to each of the phages. The data can be used to identify phage combinations capable of simultaneously treating numerous multidrug-resistant isolates.

[0134] [Table 3]

[0135] Figure 25. Data generated using bacterial impedance flow cytometry supporting the development of a susceptibility matrix for clinical isolates. A. Scatter plot showing the distribution of impedance measurements obtained from individual bacteria of strains treated with phages Ab_1, Ab_2, and Pa_1 compared to the control (no phage) after 90 minutes of treatment. B. Data analysis shows both the total cell count and the number of cells within the outlined area for each strain-phage combination. Both parameters can be important in demonstrating the susceptibility of a particular strain to a particular phage, and both can be used in combination to further delineate phage characteristics. Data represent at least two replicate experiments.

[0136] This data demonstrates the ability to rapidly define the host specificity of different isolates against phage stocks maintained within hospital laboratories that can be used to treat patients with pan-drug-resistant infections. In the example above, a patient infected with a clinical isolate similar to the MDR strain NCTC 13302 could be treated with a phage cocktail preparation containing both phages Ab_1 and Ab_2. Conversely, a patient with an infection similar to ATCC 17978 would be treated with phage Ab_2 alone. Phage-resistant bacterial isolates, such as the ATCC 17978 ColR strain (colistin-resistant), which may be present within the patient or emerge during either antibiotic or phage therapy, would be refractory to any of the phages tested. If a patient has an infection with a P. aeruginosa isolate similar to the reference strain PAO1, it is likely to respond to treatment with phage Pa_1.

[0137] Example 2: Comparative methods for assessing phage susceptibility by routine microbiology. In the absence of a bacterial impedance flow cytometry platform, the susceptibility of clinical strains to bacteriophages can be determined by classical microbiological methods. In such tests, plates containing well-isolated bacteria (time point 0; T0), such as those from clinical samples, are used to set up liquid cultures of the strain of interest in TSB or LB and grown overnight at 37°C (approximately T18h). These cultures are subcultured into fresh medium and grown for approximately 1 hour (T19h), after which bacteriophage is added. The bacteria-phage sample is then incubated under static conditions at 37°C for at least 1 hour (T20). Top agar containing TSB with 0.4-0.5% w / v agarose supplemented with 10 mM MgSO4 is melted in a microwave and allowed to equilibrate to approximately 50°C. Approximately 4 ml of top agar is added to the bacteria-phage suspension and the appropriate bacteria-only and phage-only controls, which are then immediately poured onto preheated TSB or LB plates. After solidification (approximately 1 hour; T21h), the plate is inverted and incubated overnight (Tapproximately 36h) to allow a bacterial lawn to grow. Susceptible bacterial strains are identified by the formation of plaques (holes) in the bacterial lawn, caused by phage-induced lysis of the bacteria. Partially removed or "cloudy" plaques may indicate that the phage has integrated into the bacterial chromosome, forming a temperate phage (prophage) infection. Microcolonies within the plaques may indicate the emergence of resistance during phage infection. Non-susceptible strains will not show plaque formation within the bacterial lawn.

[0138] Aside from the length of time required to assess susceptibility, typically approximately 36 h, the classical method of determining phage susceptibility is labor-intensive, and accurately determining phage susceptibility can require significant training to view and interpret the presence of plaques on plates. Similarly, identifying the emergence of resistance to phage infection can be challenging and open to interpretation.

[0139] Example 3: Assessment of phage susceptibility using bacterial impedance cytometry; phage cocktail. Phage cocktails generated by therapeutic companies or established from in-house stocks can also be evaluated using bacterial impedance flow cytometry in a manner similar to the matrix for individual phage susceptibility described in Example 1.3. The use of phage cocktails reflects the limited range of isolates of a single species that can be infected by a given phage; this is typically less than 50% of isolates for any given phage. A mixture of different phages, defined as a phage cocktail, can be used in this scenario to increase the number of clinical isolates killed by the preparation. Typically, a phage cocktail can infect and kill more than 90% of clinical isolates from a particular target species, but not all isolates. This method is likely most effective when the end user / clinician has an initial bacterial ID that allows for an initial downselection of the relevant phage cocktail, although this does not preclude the possibility of using this method directly from clinical samples based on a presumptive diagnosis of the likely pathogen in that sample (e.g., Escherichia coli or Klebsiella pneumoniae are likely the cause of a complicated urinary tract infection). In this case, bacterial isolates are incubated with one or more phage cocktails, the cocktails themselves consisting of two or more bacteriophages with different ranges of activity against different species of isolates. Such cocktails would be expected to have broader combined coverage for infection and lysis of clinical isolates than the individual component phages. Optionally, the phage cocktails are lyophilized or otherwise stored in a microfluidic device or other reaction housing, allowing phage susceptibility assays to be automated using a bacterial impedance flow cytometry reader. Bacterial isolates are prepared essentially as described in Example 1, and the bacterial suspension is incubated with the phage on the device. After an appropriate incubation period, typically 90 minutes, bacterial impedance measurements are performed and the data analyzed to obtain a simple readout of susceptibility to the phage cocktail.Metrics used can include a reduction in total cell count, a reduction in the number of bacteria within a contour within a reference profile (e.g., 95% of the untreated population), a shift of bacteria along the X-axis of a scatter plot showing the change in electrical radius (cell volume), and / or a shift on the Y-axis showing the change in electrical opacity of the bacterial membrane (membrane permittivity). Evaluation can be performed according to one or more of the aforementioned evaluation methods. This information can be used to induce treatment for infection using a phage cocktail or one of the eradication approaches described in the Examples below.

[0140] Optionally, the incubation between the phage cocktail and the bacterial isolate can be extended to assess the possibility of resistance development during treatment. This can also be automated from the microfluidic device, with a second analysis performed automatically after a prolonged incubation, such as after 8 hours.

[0141] Example 4: Workflow detailing how bacterial impedance flow cytometry phage susceptibility assessment can be used clinically, with or without prior determination of antibiotic susceptibility In current clinical practice, bacteriophage therapy is used only in scenarios where there are no available antibiotics that can successfully treat an infection. This type of use, referred to as compassionate phage therapy (cP) or emergency investigational new drug (eIND) use, is becoming increasingly common when patients are infected with essentially untreatable infections. 1~4The transition of phage therapy to a first-line treatment option is likely to occur in the future. The present invention represents a significant improvement over current methods in supporting first-line use of bacteriophages, as it allows for rapid (<4 hours), evidence-based, narrow-spectrum treatment for specific clinical indications. This "theranostic" approach incorporates an element of bacterial identification, which can use techniques for bacterial identification known in the art or can be based on other factors, such as symptoms presented by the patient or known clinical circumstances, assessed by phage lysis of clinical isolates with a defined, species-specific phage cocktail, coupled with subsequent treatment of the patient with that phage cocktail. This approach has significant benefits for the patient's microbiome, which is not expected to change significantly with pathogen-directed therapy, compared to the large-scale changes and relatively indiscriminate killing known to occur with most antibiotic classes.

[0142] In either situation, individual phage preparations or phage cocktails can be maintained within a treatment facility, such as a hospital microbiology laboratory, and deployed for the treatment of patients with unresolved infections. One non-limiting example of the use of phage therapy is as follows. The patient presents with an infection, examples of which include (but are not limited to) a urinary tract infection, bacterial pneumonia, infection associated with an implanted device, or sepsis. b. Obtain samples of body fluids from patients for routine microbiological evaluation, e.g., antimicrobial susceptibility testing and identification of the causative organism. c) Treating the patient with one or more antibiotics that are recognized as standard of care, for example according to the UK NICE guidelines, but these antibiotics fail to clear the infection within 24-48 hours and the patient's condition continues to deteriorate. d. Microbiological results identify the bacterial species using techniques such as MALDI-TOF (Bruker, Biotyper) or Gram staining or genetic analysis (DNA sequencing or DNA hybridization or PCR, etc.). This information is available within approximately 12-16 hours after presentation, during which time the patient can be treated as described in (c). The bacterium can be one of a wide range of pathogens, including, but not limited to, members of the ESKAPEE group (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, Enterobacter spp., or other members of the Enterobacteriaceae family, Escherichia coli), drug-resistant Neisseria gonorrhoeae, Stenotrophomonas maltophilia, or the Burkholderia cepacia / cenocepacia complex. e. Antibiotic susceptibility testing results, if performed, inform the range of further treatment options available to the clinician. Data using standard disk diffusion or broth dilution methods show that isolates are resistant to the majority of standard of care antibiotics, or in some cases, all antibiotics. f. Once the antibiotic susceptibility of the clinical bacterial isolate is shown to be multi-drug / pan-drug resistant, or based on species identification, a phage susceptibility impedance assay is performed essentially as described in Example 1. Results obtained within 2 hours confirm that the clinical isolate is susceptible to the phage / phage cocktail and treatment is initiated.

[0143] Phage susceptibility impedance assays can be initiated after bacterial ID is completed based on disease presentation, clinical symptoms in the patient, and known epidemiology of infection in the particular clinical setting.

[0144] Phage susceptibility assays using impedance flow cytometry can be combined with bacterial antibiotic susceptibility testing performed using the same impedance analysis technique, which will allow determination of both the antibiotic susceptibility, and, if necessary, the phage susceptibility, of an isolate within approximately 4 hours.

[0145] Combining antibiotic susceptibility and phage susceptibility impedance assays can identify synergistic combinations of phage and antibiotics that are highly effective in treating infections. This type of interaction would not be identified by other means, such as classical microbiological methods used for phage and antibiotic susceptibility measurements. Interactions between phages from any of the known phage families (including, but not limited to, phages from the families Siphoviridae, Myoviridae, Podoviridae, Ackermannviridae, Inoviridae, Leviviridae, Microviridae, and Cystoviridae) can be identified. Although synergistic effects can be observed with any antibiotic (including, but not limited to, aminoglycosides, cephalosporins, penicillins, carbapenems, tetracyclines, polymyxins, (fluoro)quinolones, oxazolidinones, macrolides, lincomycin, glycopeptides, sulfonamides, and pleuromutilins), particularly favorable synergistic interactions can be observed between lytic phages and antibiotics that generally do not penetrate Gram-negative bacteria (e.g., rifampicin, novobiocin, vancomycin, linezolid, and fosfomycin).

[0146] A single type of phage or a mixture of different phages can be used as a treatment, and a phage-sensitive impedance assay can be used to monitor the effectiveness of the treatment and to assess the emergence of resistance to the treatment.

[0147] Impedance assays can be used to monitor the effectiveness of phage therapy over time, and assay results can be used to inform the effectiveness of treatment and to dynamically modify or alter the phage library to optimize treatment, for example, to account for the emergence of resistance or further infections.

[0148] Example 5: Direct detection of phage susceptibility in bacteria in clinical samples; for example, detection of urinary tract infections from urine samples. Bacterial impedance flow cytometry can be used directly on patient samples to facilitate rapid diagnosis of infection. One iteration of this approach is the direct measurement of phage susceptibility in urinary tract infections (UTIs), pyelonephritis, or catheter-associated urinary tract infections (CAUTIs), for example, from urine samples. The presumptive diagnosis in this case is that the infection is caused by Enterobacteriaceae, most commonly species of Escherichia coli (E. coli), Klebsiella pneumoniae (K. pneumoniae), or Proteus mirabilis, and this diagnosis can be supported by local epidemiology and specific clinical symptoms (fever, positive urinary leukocyte esterase). This allows rapid phage susceptibility testing to be performed using phages / phage cocktails specific for each of these organisms.

[0149] Using an impedance assay, for example, >10 4 To comply with current clinical guidelines that define urinary tract infection based on cfu / ml urine, an initial count can be determined to determine the bacterial level in a urine sample. If necessary, the urine sample can be diluted (e.g., with media, buffers, electrolytes, or water, such as tryptic soy broth (TSB), phosphate-buffered saline (PBS), or Mueller-Hinton broth). The resulting concentration after dilution is approximately 5 x 10. 5The sample is mixed with phage or a phage cocktail preparation specific for each target species, and the sample is incubated under conditions appropriate for the target bacteria (typically, 30 minutes at about 37°C under aerobic conditions, with or without shaking). Incubation times can range, for example, from 15 to 120 minutes, but can be shorter or longer depending on the bacteria and phage. Incubation times can be at least 10 minutes, or 15 minutes or longer.

[0150] The results of impedance phage susceptibility testing allow the clinician to begin treatment of the patient with the phage preparation, either by systemic (intravenous) administration of the phage or by direct injection of the phage into the urinary tract. The effectiveness of treatment will be assessed based on a number of different responses, including resolution of the patient's symptoms, reduction in cfu in the urine, reduction in secondary measures of infection such as leukocyte esterase, and reduction in white blood cell count in the sample.

[0151] Optionally, protocols can include a means to isolate or concentrate bacteria from urine before diluting to the correct starting concentration. This can be done at the point of care or in a clinic or testing laboratory. This includes, but is not limited to, capturing bacteria on beads using physical-chemical or biochemical principles, such as polycationic or polyanionic beads, beads coated with species-specific antibodies, or generic bacterial capture ligands (e.g., mannose-binding lectins, polymyxin derivatives, vancomycin derivatives). Other capture or separation methods include those based on physical effects, such as mechanical filtration or entrapment, and acoustic, magnetic, electrical, or optical techniques.

[0152] Example 6: Detection of phage susceptibility in bacteria measured directly in clinical samples such as blood and other sterile site fluids. The concentration of bacteria in clinical samples may be too low to allow direct measurement of phage susceptibility, and the bacterial concentration may need to be increased, for example, by incubation, selective capture, or filtration, to provide enough cells to determine phage susceptibility. The current standard of care for diagnosing sepsis is culture-based, in which blood samples are collected from at least two independent sites on the body and incubated at 37°C for the presence of either aerobic or anaerobic organisms. Numerous automated systems can be used to continuously measure the growth of any bacteria in blood. These include, but are not limited to, changes in sample optical density, changes in sample impedance, oxygen utilization, carbon dioxide production, changes in volatile gases in the headspace of the culture, or other biophysical, biochemical, or chemical methods. In either case, positive blood cultures identified by these methods may be detected within 10 days. 3 ~10 4 These concentrations are expected to be greater than 0.05 cfu / ml. At these concentrations, direct analysis of phage susceptibility may be possible. To perform the assay, positive blood cultures can be processed to remove cells (including red and white blood cells and platelets), for example, via centrifugation, blood lysis, cell filtration, or any other means. The blood sample is mixed with bacterial growth medium, and phage susceptibility can be measured by impedance flow cytometry. The selection of a phage panel for evaluation may reflect the diverse range of organisms likely to cause sepsis. For example, multiple phage cocktails can be tested for susceptibility profiles. Optionally, rapid bacterial ID from blood bottles, such as the MBT Sepsityper IVD kit (Biotyper, Bruker), can be used to identify pathogens in positive blood cultures before initiating the phage susceptibility impedance protocol.

[0153] Optionally, an additional step may be introduced to isolate or subculture bacteria from blood cultures prior to analysis. This can be done at the point of care or in the clinic or testing laboratory. This includes, but is not limited to, capturing bacteria on beads using physical-chemical or biochemical principles, such as polycationic or polyanionic beads, beads coated with species-specific antibodies, or generic bacterial capture ligands (e.g., mannose-binding lectins, polymyxin derivatives, vancomycin derivatives). Other capture or separation methods include those based on physical effects, such as mechanical filtration or entrapment, and acoustic, magnetic, electrical, or optical techniques.

[0154] A similar approach can be used for other clinical samples, such as cerebrospinal fluid (CSF), synovial fluid, or samples taken from wounds. Growth and / or selective bacterial capture can provide material that can be measured by impedance flow cytometry.

[0155] Example 7: Rapid screening of phages for eradication therapy, e.g., for cystic fibrosis The species-specific nature of bacteriophages can be used as the basis for narrow-spectrum treatment for eradication. Such an approach can be utilized in chronic conditions where the acquisition or presence of a particular species of bacteria is associated with a particular component of the pathology. Alternatively, phage therapy can be used when the presence of a specific bacterium adversely affects treatment options. This approach can be used for a wide range of chronic conditions in humans and animals. Table 4 provides non-limiting examples of these conditions along with their pathogens.

[0156] [Table 4]

[0157] In the case of cystic fibrosis or other chronic lung diseases, one of many bacterial species is associated with poor patient outcomes. These species can be targeted with bacteriophage therapy selected based on impedance flow cytometry. This technique is used to rapidly assess susceptibility, allowing for rapid initiation of treatment. The assay can be provided in a high-throughput format to facilitate screening against a large number of species / strains. Target species may include, but are not limited to, Pseudomonas aeruginosa, Stenotrophomonas maltophilia, Burkholderia cepacia / cenocepacia / multivorans, Achromobacter spp., Pandoraea spp., and Ralstonia spp.

[0158] A non-limiting example of a test protocol is provided below.

[0159] Patients present with cystic fibrosis or other chronic lung infections and have had samples taken, for example, of forced sputum or bronchioloalveolar lavage (BAL).

[0160] Optionally, the sample may be evaluated using routine microbiological methods, culturing bacteria using selective media to enrich for the species of interest and, if necessary, identifying the species.

[0161] The BAL sample is mixed with growth medium and the sample is incubated with either a single phage isolate or a phage cocktail for a period of time (typically 30-120 minutes, but can be shorter or longer).

[0162] Another example is dispensing phage or phage cocktails into 96-well plates, using phage preparations covering a range of species and exhibiting different species selectivities, which can be interfaced with bacterial impedance assays using a variety of liquid handling systems.

[0163] The susceptibility of clinical isolates to phage or phage cocktails is determined using impedance flow cytometry. When the assay is performed directly on BAL samples, one or more phage preparations will affect one or more pathogens within the sample, as indicated by changes in electrical properties associated with changes in the physicochemical properties of the bacteria.

[0164] One or more phages or phage cocktails may be used to decolonize patients to significantly reduce or eradicate pathogens that have serious adverse health consequences for chronically infected patients. This is commonly used in CF patients at first presentation with Pseudomonas aeruginosa, but may be suitable for a variety of pathogens.

[0165] In alternative assays, phage-based eradication therapy can be combined with one or more antibiotics. One example of an eradication therapy that would benefit from the inclusion of selected phages is a 3-month combination treatment with nebulized colistin and oral ciprofloxacin.

[0166] Impedance cytometry can be used to monitor the success of eradication therapy by following changes in susceptibility to phage over time. This information can be used to modify phage libraries to address changes in colonization or the emergence of resistance.

[0167] Example 8: Identification of phages for enteric decontamination treatment There is growing recognition of the importance of gut colonization in the development of a range of chronic diseases; a non-exhaustive list of examples is outlined in Table 4. Selective elimination of specific pathogens from the gut is currently impossible, even with narrow-spectrum antibiotics, because they lack sufficient selectivity. Phage therapy for selectively decolonizing the gut or other microbiome is a potential solution to these challenges, but this relies on the availability of technologies that allow for rapid and high-throughput screening of phages / phage cocktails. Bacterial impedance flow cytometry is one example of such a technology, allowing both rapid and high-throughput identification of phage susceptibility as a basis for selective treatment. A suitable workflow for this approach is presented below. a. Fecal samples are collected from patients exhibiting symptoms associated with a wide range of chronic conditions, as represented by the non-exhaustive list provided in Table 4. b. The sample is cultured on selective plates to enrich for the target pathogen that is the target of phage-based elimination therapy. Bacteria are suspended in bacterial growth medium and incubated with phage / phage cocktail for a predetermined period of time. c. The susceptibility of the target organism to the specific phage preparation is determined using bacterial impedance flow cytometry methods. Phages that are effective against the specific target strains harbored by the patient are prepared for use in therapy. The phage cocktail is administered orally using an encapsulation method that protects the phage from the acidic environment of the intestine. Alternatively, the phage preparation is delivered directly to the small or large intestine or other locations within the GI tract. d. The effectiveness of phage-based elimination therapy can be assessed by repeated fecal sampling and selective culture to monitor for the presence of the pathogen or replacement of strains producing virulent / harmful gene products with more benign strains. e. Optionally, phage-based elimination therapy may be performed in conjunction with the therapeutic use of one or more probiotics. f. In some cases, phage-based elimination therapy is a precursor to subsequent therapy to treat the underlying chronic condition, as in the selective elimination of certain species (e.g., K. pneumoniae) that express a form of cytidine deaminase prior to cancer therapy using compounds such as gemcitabine. This form of the enzyme inactivates chemotherapeutic drugs, reducing their activity, and thus elimination therapy potentially improves treatment outcomes for various pancreatic and lung cancers.

[0168] Example 9: Pretreatment of fecal transplant material to eliminate pathogens associated with chronic disease Fecal transplants have proven to be a highly effective treatment for recurrent attacks of disease caused by Clostridium difficile and are currently used to treat enterocolitis. 29 , chronic liver disease 30 and irritable bowel disease 31 In a similar manner to the examples detailing the selective elimination of problematic bacteria from the intestine, a similar phage-based elimination approach could be used with fecal transplant material prior to transplantation into the colon, obviating potential challenges associated with reintroducing chronic disease-causing bacteria that have been linked to adverse outcomes. 32 While this can be achieved in some cases by screening, the ability to selectively eradicate problematic bacteria increases the flexibility and effectiveness of fecal transplant approaches.

[0169] This workflow is essentially the same as the intestinal elimination example described above (Example 8), except that fecal material is handled ex vivo and treated with phages selected to eliminate specific bacterial species prior to implantation.

[0170] Example 10: Treatment of infectious diseases where phage delivery of resistance-busting factors is essential for mediating susceptibility to antibiotics. Phages are increasingly being used as delivery vehicles for a range of antibacterial agents and antibiotic subversives that require gene expression within bacteria. Examples of genetically encoded antibacterial agents include small acid-soluble spore proteins (SSPs). 33 , transcription factor decoy 34 These include various antibiotic resistance breakers, such as β-lactamase inhibitors, modulators of efflux pump expression, etc. The effectiveness of these molecules as antibacterial agents depends on the ability of the phage to infect the target species, and therefore there remains a need to rapidly determine phage susceptibility.

[0171] An example method is as follows: a clinical isolate from an infection site is mixed with either a genetically engineered phage carrying an antimicrobial gene or a base phage that is the basis of a delivery vector. Incubation of the phage with the target is performed as described above, and bacterial impedance is measured and analyzed. Results indicating any phage-mediated lysis are analyzed as previously described. The time to expression of the antimicrobial gene may mean that the rapid assay format does not measure the effect of gene expression. Impedance measurements will also reflect the gene-based antimicrobial effect, if it contributes. In some cases, the effect of genes affecting antibiotic resistance will only be exerted in the presence of the antibiotic and phage-mediated infection.

[0172] Example 11 1. Use of the Serum Bactericidal Assay in the Clinical Setting Serum bactericidal assays are used to assess the ability of a patient's blood to kill a pathogen of interest. This can be used in a series of assays to assess either naturally occurring antibody levels or antibodies generated by either active (vaccination) or passive (immunotherapy with preformed antibodies) immunization. This activity forms an essential part of a patient's defense against pathogens and often works in conjunction with other treatments (e.g., antibiotics, phages). This type of measurement can be particularly important in situations where infection may be present in a non-peripheral wound, such as can be observed in endocarditis, meningitis, prosthetic joint infection, or osteomyelitis. Similarly, measuring these types of activity can be important in infections in neutropenic or other immunocompromised patients.

[0173] While these are valuable assays in the context of antibody-mediated killing, they are not routinely used in clinical settings as a primary readout. This reflects the difficulty of performing these assays and the lack of standardized methods that can provide real-time data (i.e., not dependent on external laboratory analysis). Culture-based laboratory analysis for the presence and enumeration of viable bacteria, typically over 24 h but potentially up to 48–72 h for slow-growing species, also limits the usefulness of the method. The assay measures the lowest dilution of patient serum that sufficiently kills the target pathogen causing the infection, often expressed as a dilution factor (e.g., 1:8, 1:16).

[0174] In some cases, the effectiveness of serum bactericidal assays can be used to evaluate antibiotic and serum killing combinations, where the antibiotic is added to the serum at a defined concentration before the assay is performed. This conceptually supports the development and use of antibiotics that act in a manner complementary to antibody-mediated killing.

[0175] The bacterial impedance flow cytometry assay can be used to measure serum bactericidal activity rapidly and in a near-patient setting to aid clinical decision making. The following is a workflow that can be used with the assay in a clinical setting. A patient presents in the clinic with an infection associated with potential endocarditis, for example, after cardiac surgery. The pathogen causing the infection is identified by either culture-based or molecular methods. The pathogen can be one of a range of pathogens, including, but not limited to, Staphylococcus species, Streptococcus species, or Enterococcus species. b. Prepare a culture of the pathogen in cation-adjusted Mueller-Hinton broth by picking three colonies from the plate. The concentration of bacteria is approximately 5 x 10 5 Correct to cfu / ml. c. Bacteria are added to an equal volume of patient serum diluted in standard ultrafiltered human serum, and the bacteria / serum is incubated for 1 hour at 37° C. in the presence of 5% CO 2 . d. The sample is evaluated using a bacterial impedance assay, which measures both the number of viable bacteria in the sample and any changes in the impedance profile that may indicate serum-mediated bacterial lysis prior to death. Comparison of the sample with an untreated bacterial population will also allow for the identification of antibody binding. e. Serum titers that kill >99.5% of the bacteria in a sample can indicate a likely clinical outcome; patients with high peak titers (e.g., a 1:32 dilution positive for killing at the required rate) are more likely to be able to clear the infection than patients with low peak titers (e.g., 1:2 dilutions or greater). This information can be used to modify treatment options or explore surgical intervention options. f. Optionally, the method can be used to monitor the effectiveness of vaccination programs aimed at increasing serum concentrations of antibodies against specific pathogens to generate a protective bactericidal antibody response. In this case, serum samples from patients pre- and post-vaccination are serially diluted and incubated with the target pathogen as described above. A bacterial impedance flow cytometry assay is performed to quantify the number of viable cells. An increase in antibody titer after vaccination will correlate with satisfactory killing achieved at higher dilutions of patient serum (e.g., 1:128 compared to 1:8 pre-vaccination). g. Optionally, the bacterial impedance flow cytometry method is used to identify multidrug-resistant pathogens (e.g., P. aeruginosa) 35 A novel approach would provide a rapid readout that allows for monitoring serum levels of passively administered antibodies, a treatment targeting the Bacterium difficile (B. difficile ). In this case, the methods described above would be used to optimize the administration of the monoclonal antibody product to ensure that the serum dilution that effectively kills the target strain is maintained above a predetermined threshold. This ensures that there is sufficient circulating antibody to effectively minimize the spread of the bacteria and / or prevent cytotoxicity caused by the production of any toxins or endotoxins by the bacteria.

[0176] Example 12: Bacterial impedance flow cytometry methods are used to determine the effectiveness of membrane-permeable peptide antimicrobial agents in achieving bacterial killing. Antimicrobial peptides (sometimes referred to as host defense peptides), bacteriocins, lanthipeptides, pyocins, phage-derived endolysins, endopeptidases, and muralic proteins (e.g., artilisin) have all been proposed as candidates for the development of new antimicrobial agents. Many of these biologics have narrow-spectrum activity and can be tailored to be specific to particular species of bacteria, rather than broad-spectrum activity that could potentially damage the microbiome. This is similar to the method used in phage therapy, and therefore provides a natural synergy with bacterial impedance flow cytometry methods.

[0177] The method for determining the efficacy of different membrane-permeable peptide antimicrobial agents is essentially the same as in Example 1. Briefly, colonies are picked from plates bearing bacteria from clinical samples (e.g., urine samples from suspected UTIs) into tryptone soy broth (TSB) and incubated for 30 minutes before adding the membrane-permeable peptide antimicrobial preparation. Incubation is typically performed at 37°C with shaking. Bacteria are cultured in TSB at approximately 5 x 10 5 The samples are diluted to a concentration of 1000 cfu / ml and supplemented with representative examples of cationic antimicrobial peptides (cAMPs), such as pleurocidin and α-helical pore-forming peptide (melittin). Concentrations are selected to span the minimum inhibitory concentrations of the two strains, so that they can be used clinically for antimicrobial breakpoint determination. Optionally, bacterial impedance flow cytometry methods can be used to generate minimum inhibitory concentration measurements, or fixed concentrations based on resistance / susceptibility breakpoints are used. Samples are incubated at 37°C for 30 or 60 minutes in a 37°C static incubator. Populations at each time point are analyzed using bacterial impedance flow cytometry, and data are collected and analyzed to measure both viable cell counts and any shift in the cell population from a contour encompassing the percentage of a control or untreated population of the same species.

[0178] Both peptides tested produced rapid bactericidal kill, resulting in a >5-log reduction in viable bacterial counts within 4 hours through membrane disruption (both peptides) and interaction with one or more intracellular targets (cAMP only). At the measured time points, it was possible to identify a time dependence of the number of bacteria remaining within the contour, with shifts in the scatter plots consistent with membrane disruption caused by the peptides. This clearly distinguished the population response to the high and low concentrations of peptide used in the study, consistent with the relative sensitivity of the bacteria to the two peptides.

[0179] When used in a clinical setting, this would allow rapid determination of the susceptibility of strains causing infection and provide information for direct treatment with these peptides.

[0180] Figure 26 shows that different types of antimicrobial peptides induce rapid changes in bacterial impedance at supra-inhibitory concentrations but not at sub-inhibitory concentrations. Two different types of antimicrobial peptides, cationic AMP (cAMP; a membrane-permeable peptide, a D-amino acid version of pleurocidin from winter flounder) and an α-helical peptide (melittin; a pore-forming peptide), were incubated with Escherichia coli (NCTC 12923) and Klebsiella pneumoniae (NCTC 13368) at supra-inhibitory (high; cAMP 16 μg / ml and melittin 128 μg / ml) and sub-inhibitory (low; cAMP 0.25 μg / ml and melittin 4 μg / ml) concentrations for 30 or 60 minutes. The bacterial impedance of the populations was measured. Scatter plots show rapid migration of bacteria from the contour defined by the untreated population within 30 minutes at supra-inhibitory concentrations, but not at sub-inhibitory concentrations, with both peptides and species tested. NCTC 13368 exhibits less sensitivity to melittin than NCTC 12923, but results are comparable for cAMP at the concentrations tested. Results are representative of at least two experiments conducted independently by the inventors. The various embodiments described herein are presented solely to aid in the understanding and teaching of the claimed features. These embodiments are provided only as a representative sample of embodiments and are not intended to be exhaustive and / or exclusive. The advantages, embodiments, examples, features, characteristics, structures, and / or other aspects described herein should not be construed as limitations on the scope of the invention, as defined by the claims, or equivalents of the claims, and it should be understood that other embodiments may be utilized and modifications may be made without departing from the scope of the claimed invention. Various embodiments of the present invention may comprise, consist of, or consist essentially of any suitable combination of the disclosed elements, components, features, parts, steps, means, etc., other than those specifically described herein. In addition, the present disclosure may include other inventions not currently claimed, but which may be claimed in the future.

[0181] Example 13. A. baumannii (NCTC 13302) was incubated with phage essentially as described in Example 1, except that a multiplicity of infection (MOI) of 0.01, 0.1, or 1 was used. Bacterial impedance flow cytometry profiles were measured every 30 minutes for 2 hours for untreated and treated samples. Figure 27 shows bacterial impedance flow cytometry profiles of A. baumannii (NCTC 13302) 2 hours after treatment for untreated or phage-treated samples. Scatter plots show the distribution of impedance measured for individual bacteria in untreated samples (A, MOI = 0) and samples treated with an MOI of 1 (B), 0.1 (C), or 0.01 (D). A contour encompassing 50% of the untreated population was calculated for each time point. The number of individual bacteria within this contour was counted for each MOI (0, 0.01, 0.1, 1). Figure 28 shows the variation in cell number compared to the untreated cell population (black) for populations treated with an MOI of 1 (dark gray), an MOI of 0.1 (medium gray), and an MOI of 0.01 (light gray) at time points: A: 30 min; B: 1 hr; C: 1 hr 30 min; D: 2 hr. The population inoculated with an MOI of 1 shows a decrease at each time point, while the population inoculated with an MOI less than 1 initially decreases slightly compared to the untreated population, then returns to at least the level of the untreated population.

[0182] Example 14: Evaluation of resistance emergence to either phages or antimicrobial peptides. An important factor in determining the suitability of a phage or phage cocktail for treatment of a bacterial isolate is the assessment of whether resistance may emerge rapidly during treatment and adversely affect treatment outcome.

[0183] In this case, clinical isolates of bacteria are incubated with phage essentially as described in Example 1. An initial assessment of phage susceptibility can be made within 90 or 120 minutes for rapidly growing bacteria and phage with short incubation periods. By continuing to evaluate bacterial impedance flow cytometry values ​​over an extended period, in this case measuring the impedance profile hourly for up to 6 hours and comparing the data with the initial readings, it is possible to determine whether there is a subset of bacteria in the population that remains within the gated region identified from the control, untreated, or reference population. If the number of bacteria within this contour increases despite the generation of new progeny phage and rounds of reinfection, this likely indicates a mutation leading to resistance that makes the selection of this phage for therapy unsafe. A similar effect is observed, for example, in Example 13, when a low multiplicity of infection (MOI<1) of phage is administered and the number of bacteria within the gated region increases after an initial decrease.

[0184] The emergence of this resistance is evident at a single bacterium level, such as impedance flow cytometry, at a much earlier time point than can be achieved with other techniques, allowing more accurate and timely decisions to be made about the suitability of phages for therapy.

[0185] It is possible to simulate this situation of natural phage resistance emergence by spiking a low frequency of resistant phage into a generally susceptible population of the same strain.

[0186] A similar approach can be taken to assess the emergence of resistance to antimicrobial peptides by serially sampling bacterial populations treated as in Example 12 over a 4-6 hour period, which will also help inform treatment strategies for specific clinical isolates and clinical conditions.

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Claims

1. 1. A method of impedance flow cytometry comprising: flowing a sample of a fluid containing particles suspended in an electrolyte along a flow channel; applying an electrical signal to a current path through the fluid, the current path comprising at least a first current path, a second current path, a further first current path, and a further second current path, the electrical signal applied to the first current path and the further first current path having a frequency, a magnitude, and a phase, and the electrical signal applied to the second current path and the further second current path having a frequency, a magnitude, and an opposite phase to the electrical signal applied to the first current path and the second current path; detecting a current in the current path; generating a first summed signal representative of a sum of currents detected in the first current path and the second current path, and a second summed signal representative of a sum of currents detected in the further first current path and the further second current path; obtaining a differential signal representing a difference between the first summed signal and the second summed signal; The method, wherein the particles are microorganisms, and the microorganisms have been exposed to one or more antimicrobial agents selected from the group consisting of phages, serum components, immune system components, and antimicrobial peptides.

2. The method described in claim 1, wherein the antimicrobial peptide is a membrane-permeable peptide, a membrane-disrupting peptide, or a pore-forming peptide antimicrobial agent.

3. The method described in claim 1, wherein the microorganism is a bacterium.

4. The bacterium i) members of the ESKAPE group (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, Enterobacter spp or other members of the Enterobacteriaceae family, Escherichia coli), ii) drug-resistant Neisseria gonorrhoeae; iii) Stenotrophomonas maltophilia, or iv) Burkholderia cepacia / cenocepacia complex; The method of claim 3, wherein

5. The method of claim 3 or 4, wherein the bacteria have been exposed to a lytic phage.

6. 6. The method of any one of claims 1 to 5, wherein the method further comprises identifying the bacterial species in the sample by detecting phage lysis using a defined species-specific phage cocktail.

7. the one or more antimicrobial agents comprise a phage or phage cocktail specific for Enterobacteriaceae, and the method comprises detecting the presence of phage lysis in an isolated patient sample using the phage or phage cocktail; The method of any one of claims 1 to 6, wherein the presence of phage lysis indicates that the patient is suffering from a urinary tract infection, pyelonephritis or catheter-associated urinary tract infection (CAUTI).

8. 8. The method of claim 7, wherein the Enterobacteriaceae is selected from E. coli, K. pneumoniae, and Proteus mirabilis.

9. The method further includes providing a graph plotting one or more components of impedance values ​​of a control sample comprising bacteria that have not been exposed to phage; 9. The method according to any one of claims 1 to 8, wherein a contour enclosing 50% of the bacteria in the control sample is established on the graph and the number of particles (bacteria) in the (test) sample that lie within said contour is determined.

10. The method of any one of claims 1 to 9, wherein the method further comprises determining a cell count for the number of bacteria in the sample.

11. The method of any one of claims 1 to 10, further comprising calculating an impedance signal from the differential signal, the impedance signal representing one or more components of the impedance value of the particle.

12. The method of claim 11 , further comprising plotting the one or more components of the impedance values ​​of the particles on a graph to show the distribution of the particle population.

13. 13. The method of claim 12, further comprising establishing an outline on the graph indicating a boundary of the distribution of the population, the boundary enclosing a major percentage of data points, the percentage being 99%, 95%, 90%, 75%, or 50% such that outlying measurements are excluded.

14. 14. The method of claim 13, further comprising acquiring a differential signal and calculating an impedance signal for a further sample of fluid to plot a graph of impedance values ​​for particles in the further sample, and comparing a distribution of the population of particles in the further sample to the contour to identify any differences between the particles in the sample and the particles in the further sample.

15. 15. The method of claim 14, wherein the particles in the sample and the particles in the further sample are two groups of the same microorganisms, the microorganisms in the sample have not been exposed to an antimicrobial agent, and the microorganisms in the further sample have been exposed to an antimicrobial agent, and identifying a difference between the particles in the sample and the particles in the further sample indicates susceptibility of the microorganisms to the antimicrobial agent.

16. 16. The method of claim 15, further comprising acquiring a differential signal and calculating impedance signals for additional additional samples, each of the additional samples comprising the same group of microorganisms exposed to either (a) different concentrations of the same antimicrobial agent, whereby identification of a difference indicates a minimum concentration of the antimicrobial agent to which the microorganisms are susceptible, or (b) different antimicrobial agents.

17. 15. The method of claim 14, wherein the particles in the sample and the particles in the further sample are microorganisms in a subsample of the same sample, the sample including an antimicrobial agent to which the microorganisms are exposed, the differential signal being acquired for two or more time intervals while the sample is continuously flowing along the flow channel, each time interval corresponding to a different subsample, and a first time interval covering a time immediately after exposure of the microorganisms to the antimicrobial agent being designated as corresponding to a subsample in which the microorganisms are unaffected by the antimicrobial agent.

18. 18. The method of any one of claims 12 to 17, wherein the one or more components of the impedance value include a magnitude and a phase of the impedance value for a single frequency of the electrical signal.

19. 18. The method of any one of claims 12 to 17, wherein the frequency of the electrical signal comprises at least two frequency components, and the one or more components of the impedance value comprise a magnitude of the impedance value at a first frequency component and a magnitude of the impedance value at a second frequency component.

20. 20. The method of claim 19, wherein the first frequency component comprises a low frequency and the second frequency component comprises a high frequency that is higher than the low frequency.

21. 21. The method of claim 20, wherein the first frequency component is at a frequency below 10 MHz and the second frequency component is at a frequency above 10 MHz.

22. 22. The method of claim 20 or claim 21 when dependent on claims 14 to 17, wherein identifying any differences comprises identifying a change in the distribution of impedance values ​​at said low frequencies, which is indicative of a change in microbial size.

23. 22. The method of claim 20 or claim 21 when dependent on claims 14 to 17, wherein identifying any differences comprises identifying changes in the distribution of impedance values ​​at said high frequencies, which are indicative of changes in morphology of the microorganisms.

24. 12. The method of claim 1 or claim 11, further comprising analysing the differential signal, or the impedance signal if calculated, to identify patterns known to be caused by the presence of particles flowing through the current path, and counting the number of occurrences of the patterns to determine the number of particles in the sample.

25. 12. The method of claim 1 or claim 11, further comprising measuring the magnitude of the differential signal, or the impedance signal if calculated, and calculating the size of the particle from the measured magnitude.

26. A method according to any preceding claim, wherein the current path is substantially transverse to the direction of flow of the fluid sample along the flow channel.

27. A method according to any preceding claim, wherein the current path is substantially along the direction of flow of the fluid sample along the flow channel.

28. 26. The method of any one of claims 1 to 25, wherein one of the first current path and the second current path and one of the further first current path and the further second current path are substantially transverse to a direction of flow of the fluid sample along the flow channel, and the other of the first current path and the second current path and the other of the further first current path and the further second current path are substantially along the direction of flow of the fluid sample along the flow channel.

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