Patent Publication Number: US-2023140713-A1

Title: Rapid screen for antibiotic resistance and treatment regimen

Description:
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. 
     Antimicrobial resistance (AMR) is the ability of a microorganism to avoid, modify or adapt to the adverse effects of an antimicrobial agent used against it. Of particular concern is a rise in, and global spread of, resistant bacteria, which is now recognised as a leading threat to the health and wealth of the world&#39;s population. When an infection is suspected, a doctor often immediately prescribes antimicrobial agents with the aim of promptly providing effective treatment. However, in many cases the antimicrobial agents are either not needed, or are inappropriate for the particular infection-causing organism. One notable problem is treatment of bacterial infections with antimicrobial agents which are ineffective owing to the presence of resistance mechanisms. This can mean the infection may persist, increase in severity and possibly spread to other patients. A leading reason for the rapid prescribing of potentially ineffective antimicrobial agents is that laboratory tests for checking antimicrobial resistance traits are far too slow to be useful in informing antimicrobial prescribing when the patient initially presents for treatment. 
     Typically, antimicrobial susceptibility tests measure microbial growth in the presence of antimicrobial agents in liquid cultures or on solid agar plates. A common test known as a disk diffusion test (or quantitative variations of this test principle called Etests) requires that a microbial culture be grown overnight to obtain a sample which is then placed on an agar plate. Discs or strips containing known concentrations of antimicrobial agents are placed on the agar plate, and the inhibition of microbial growth close to the discs or strips containing antimicrobial agents is measured after a long incubation period. The broth microdilution method measures the growth of microorganisms in liquid cultures with different concentrations of antimicrobial agents to determine the antimicrobial concentration at which microbial growth is inhibited (known as the minimum inhibitory concentration, or MIC). The broth microdilution MIC method may be performed using automated laboratory equipment. These conventional assays measure the growth of populations of microorganisms over time and take many hours to perform. The results cannot therefore be used to inform or guide prescription in the early stages of infection, when that guidance is most important. 
     As an alternative to these conventional tests which measure populations of microorganisms, analysing the optical properties of single microorganisms exposed to antimicrobial agents has been demonstrated to correlate closely with the antimicrobial susceptibility measured with the conventional tests, but within a shorter time window of less than one hour (WO 2012/164547). Commonly, a population of microorganisms is exposed to an antimicrobial agent for a fixed duration of time, typically thirty 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 with an optical flow cytometer, which detects light scattered from the microorganisms in a forward direction that indicates particle size, and a fluorescence signal corresponding to microorganisms. The optical data are compared with data obtained from a population of the same sample of microorganism, also stained with dye but which has not been exposed to the antimicrobial agent. Differences in the data from the two samples indicate whether the microorganisms are susceptible to the agent. Additionally, exposure of samples to a series of different antimicrobial concentrations is used to determine a minimum dose of antimicrobial agent required to effectively inhibit the microbial growth. Optical cytometry has a number of drawbacks. The use of dyes typically requires one or more wash steps in the procedure, which limits the scope for miniaturising and automating the test procedure. Removal of the antimicrobial agent by washing prior to addition of the dye suspends the antimicrobial treatment at that moment, so preventing continuous measurements of antimicrobial effects on a single sample over time. Optical cytometers are bulky and very costly, and require manipulation techniques such as hydrodynamic and/or acoustic focusing to correctly position the microorganisms within an optical analysis zone. The fluorescent dyes are also expensive. Hence, optical cytometry is not well-suited for the analysis of antimicrobial susceptibility at the point of need. 
     New approaches able to increase the speed and reduce the cost of the analysis of antimicrobial susceptibility testing, and hence guide appropriate antimicrobial prescription, are therefore required. 
     SUMMARY OF THE INVENTION 
     Aspects and embodiments are set out in the appended claims. 
     Provided herein are methods for antimicrobial agent susceptibility testing comprising preparing one or more samples of microorganisms suspended in an electrolyte, comprising 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 impedance values of the microorganisms exposed to the antimicrobial agents; comparing the first impedance signal and a reference impedance signal; and determining a susceptibility of the microorganisms to the antimicrobial agents based on any differences between the first impedance signal and the reference impedance signal, wherein the antimicrobial agent is one or more selected from the group of phage, a serum component, immune system components, and antimicrobial peptides, preferably where said antimicrobial peptides are membrane penetrating peptide, membrane disrupting peptide or pore forming peptide antimicrobials. The reference signal may be obtained by preparing a second sample of the microorganism exposed to an antimicrobial agent and passing the second sample through the impedance flow cytometer to obtain a second impedance signal representing one or more components of the impedance values of the exposed microorganisms. The reference signal may be a predetermined value for one or more components of the impedance values included in the first impedance signal, optionally wherein the component is Electrical size (X-axis on scattergrams in the Examples) and/or Electrical opacity (Y-axis on scattergrams in the Examples). The reference impedance signal may be a threshold and said determining a susceptibility may include comparing the first impedance signal to the threshold.
 
According to an aspect of certain embodiments described herein, there is provided a method of antimicrobial agent susceptibility testing comprising: preparing samples of microorganisms suspended in an electrolyte, comprising a first sample of the microorganisms unexposed to antimicrobial agents and a second sample of the 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 impedance values 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 values of the exposed microorganisms; comparing the first impedance signal and the second impedance signal; and determining a susceptibility of the microorganisms to the antimicrobial agent based on any differences between the first impedance signal and second impedance signal wherein the particles are microorganisms and wherein said microorganisms having been exposed to an antimicrobial agent selected from the group of phage, a serum component, immune system components, and antimicrobial peptides, preferably wherein said antimicrobial peptides are membrane penetrating peptide, membrane disrupting peptide or pore-forming peptide antimicrobials.
 
     According to an aspect of certain embodiments described herein, there is provided a method of impedance flow cytometry comprising: flowing a sample of fluid comprising particles suspended in an electrolyte along a flow channel; 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, wherein the electrical signals applied to the first current path and the further first current path have a frequency, magnitude and phase and the electrical signals applied to the second current path and the further second current path have substantially equal frequency and magnitude and opposite phase to the electrical signals applied to the first current path and the second current path; detecting current flow in the current paths; producing a first summed signal representing the sum of the current flow detected in the first current path and the second current path, and a second summed signal representing the sum of the current flow detected in the further first current path and the further second current path; and obtaining a differential signal representing the difference between the first summed signal and the second summed signal wherein the particles are microorganisms and wherein said microorganisms having been exposed to an antimicrobial agent selected from the group of phage, a serum component, immune system components, and antimicrobial peptides, preferably wherein said antimicrobial peptides are membrane penetrating peptide, membrane disrupting peptide or pore-forming peptide antimicrobials. 
     These and further aspects of certain embodiments are set out in the appended independent and dependent claims. It will be appreciated that features of the dependent claims may be combined with each other and features of the independent claims in combinations other than those explicitly set out in the claims. Furthermore, the approach described herein is not restricted to specific embodiments such as set out below, but includes and contemplates any appropriate combinations of features presented herein. For example, methods may be provided in accordance with approaches described herein which includes any one or more of the various features described below as appropriate. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       For a better understanding of the invention and to show how it may be carried into effect, reference is now made by way of example to the accompanying drawings in which: 
         FIG.  1    shows a schematic cross-sectional side view of an example impedance flow cytometry apparatus; 
         FIG.  2    shows a schematic cross-sectional side view of part of the apparatus of  FIG.  1   ; 
         FIGS.  3 ( a ) to ( c )  show graphs of current against time and differential current against time measured with the apparatus of  FIGS.  1  and  2   ; 
         FIG.  4    shows a schematic cross-sectional side view of an electrode and circuitry configuration for an impedance flow cytometer according to a first example of an alternative electrode arrangement; 
         FIG.  5 ( a ) to ( c )  shows graphs of summed current against time and differential summed current against time measured by a method using the apparatus of  FIG.  4   ; 
         FIG.  6    shows a schematic cross-sectional side view of an electrode and circuitry configuration for an impedance flow cytometer according to a second example; 
         FIG.  7    shows a schematic cross-sectional side view of an electrode and circuitry configuration for an impedance flow cytometer according to a third example; 
         FIG.  8    shows a schematic cross-sectional side view of an electrode and circuitry configuration for an impedance flow cytometer according to another example; 
         FIGS.  9 ( a ) and ( b )  show schematic depictions of the interaction of a cell with an electric field at low and high frequencies; 
         FIG.  10 ( a ), ( b ), ( c ) and ( d )  show example scatter plots of impedance data recorded from bacterial cell samples at two frequencies with an impedance flow cytometry method according to an example of the present disclosure, showing an antimicrobial effect on susceptible and resistant bacteria strains; 
         FIGS.  11 ( a ) and ( b )  show example scatter plots of impedance data recorded from bacterial cell samples at two frequencies with an impedance flow cytometry method according to an example of the disclosure, showing a further effect of antimicrobial agent on susceptible bacteria. 
         FIGS.  12 ( a ) and ( b )  show example scatter plots of impedance magnitude and phase data recorded from bacterial cell samples at one frequency with an impedance flow cytometry method according to an example of the present disclosure; 
         FIGS.  13 ( a ) and ( b )  show example scatter plots of impedance magnitude and phase data recorded from bacterial cell samples at two frequencies with an impedance flow cytometry method according to an example of the present disclosure; 
         FIG.  14 ( a ) to ( f )  shows example scatter plots of impedance data recorded from bacterial cell samples at two frequencies with an impedance flow cytometry method according to an example of the present disclosure, showing an effect of different concentrations of antimicrobial concentrations on a susceptible bacteria strain; 
         FIG.  15 ( a ) to ( d )  shows graphs of the variation of several bacteria cell characteristics with concentration of antimicrobial exposure, obtained with an impedance flow cytometry method according to an example of the present disclosure; 
         FIG.  16    shows a sequence of scatter plots of impedance data recorded continuously over time from a single sample of bacteria exposed to an antimicrobial agent using an impedance flow cytometry method according to an example of the present disclosure. Each plot represents a one minute window from time=0 to time=28 minutes. The Y-axis shows Electrical opacity (|Z 40 MHz |/|Z 5 MHz |) marked in increments of 0.2 from 0.6 to 1.0. The X-axis shows Electrical radius |Z 1/3   5 MHz | marked in increments of 0.5 from 1.5 to 3; 
         FIG.  17    shows a schematic cross-sectional side view of an electrode and circuitry configuration for an impedance flow cytometer according to an example with differently orientated current paths; 
         FIG.  18    shows an example scatter plot of impedance magnitude data obtained using an impedance flow cytometry method in an apparatus such as the  FIG.  17    example; 
         FIG.  19    shows bar charts of the results of bacterial cell populations treated with antibiotics at concentrations predefined for breakpoint analysis of susceptibility and resistance, measured using impedance flow cytometry; 
         FIG.  20    shows scatter plots of impedance data recorded from a variety of bacterial cell samples exposed to various antibiotics at predefined breakpoint analysis concentrations together with a bar chart of the corresponding cell populations of each sample; 
         FIG.  21    shows a time course of bacterial impedance flow cytometry profiles for, A. susceptible (NCTC 13302) and, B. non-susceptible (NCTC 10303) strains of  A. baumannii  treated with Phage Ab_2. Scatterplots show the distribution of the impedance measured for individual bacteria at 15 minutes (T15) 30 (T30), 45 (T45), 60 (T60), 75 (T75) and 90 minutes (T90). The Y-axis shows Electrical phase (40M Hz) fora range 0 to 1 in increments of 0.5. The X-axis shows Electrical radius (∥Z| 1/3   5 MHz |) marked in increments of 0.5 from 1 to 3.5; 
         FIG.  22    shows the reduction in the total cell count (A) and increase in cell size (B) for the susceptible strain (shown on right hand side at each time point in grey) compared to the resistant strain (shown on left hand side at each time point in black); 
         FIG.  23    shows the effect of treatment of a susceptible population of microorganisms with a high phage concentration over a one hour time course. Bacterial impedance flow cytometry profiles were obtained at 0 (T0), 15 (T15), 30 (T30), 45 (T45) and 60 minutes (T60).  FIG.  23 A  presents bacterial impedance flow cytometry profiles obtained from a sample of the susceptible strain after treatment with a high phage concentration.  FIG.  23 B  presents bacterial impedance flow cytometry profiles obtained from a sample of the same susceptible strain which was not treated with phage. The Y-axis shows Electrical phase (40 MHz) over a range 0 to 1 in increments of 0.5. The X-axis shows Electrical radius (∥Z| 1/3   5 MHz |) marked in increments of 0.5 from 1 to 3.5; 
         FIG.  24    shows the reduction in the total cell count (A) and increase in cell size (B) for a susceptible bacterial strain treated with phage (shown on right hand side at each time point in grey) compared to the same strain without phage infection (shown on left hand side at each time point in black) over a 60 minute time course; 
         FIG.  25    shows bacterial impedance flow cytometry data used to determine the phage susceptibility of potential clinical isolates. A. Scattergrams showing the distribution of impedance measurements taken from individual bacteria of strains treated with phage Ab_1 (second row), Ab_2 (third row) and Pa_1 (bottom row) compared to control (top row, no phage) after 90 minutes treatment. The Y-axis shows Electrical opacity (|Z 40 MHz |/|Z 5 MHz |) marked in increments of 0.2 from 0.6 to 1.0. The X-axis shows Electrical radius |Z 1/3   5 MHz | marked in increments of 0.5 from 1.0 to 3.5 B. The data analysis shows both the total cell count (upper panel) as a percentage of the control and the cell count within the contoured region (lower panel) as a percentage of the control for each strain-phage combination: phage Pa_1 (left hand column); phage Ab_1 (middle column); and phage Ab_2 (right column); 
         FIG.  26    shows that different types of antimicrobial peptide cause a rapid change in the bacterial impedance at supra- but not sub-inhibitory concentrations.  FIG.  26 A  shows the susceptibility of  E. Coli  NCTC 12923 and  FIG.  26 B  shows the susceptibility of  E. coli  NCTC 13368 to a cationic AMP (cAMP) and an alpha helical peptide (melittin). Scattergrams show the distribution of impedance measurements taken from individual bacteria of strains treated with the peptides compared to control. The Y-axis shows Electrical opacity (|Z 40 MHz |/|Z 5 MHz |) marked in increments of 0.2 from 0.6 to 1.0. The X-axis shows Electrical radius |Z 1/3   5 MHz | marked in increments of 0.5 from 1.0 to 3.5. The data analysis shows both the total cell count (upper panel) as a percentage of the control and the cell count within the contoured region (lower panel) as a percentage of the control for each strain-peptide combination. 
         FIG.  27    Scattergrams showing the distribution of impedance measurements taken from  A. baumannii  (NCTC 13302) after 2 hours of growth, either (A) untreated (307 cells in gated region), or treated with phage at different multiplicity of infections: (B) MOI=1, 144 cells in gated region; (C) MOI=0.1, 317 cells in gated region; D MOI=0.01, 333 cells in gated region. The Y-axis shows Electrical opacity (|Z 40 MHz |/|Z 5 MHz |) marked in increments of 0.2 from 0.4 to 1.2. The X-axis shows Electrical radius |Z 1/3   5 MHz | marked in increments of 0.5 from 1.0 to 3.5. The gated region is the region enclosed by a contour enclosing 50% of the untreated population. 
         FIG.  28    shows the variation in cell count compared to an untreated population of cells (black, first column on the left) for populations treated with an MOI of 1 (dark grey, second column from left), an MOI of 0.1 (mid grey, third column from left) and an MOI of 0.01 (light grey, right hand column) at time points of A: 30 mins (Y axis: 0-10000 cells in contour); B: 1 hour (Y axis: 0-1600 cells in contour); C 1 hour 30 mins (Y axis: 0-2000 cells in contour); D 2 hour (Y axis: 0-350 cells in contour). 
     
    
    
     DETAILED DESCRIPTION 
     Aspects and features of certain examples and embodiments are discussed/described herein. Some aspects and features of certain examples and embodiments may be implemented conventionally and these are not discussed/described in detail in the interests of brevity. It will thus be appreciated that aspects and features of apparatus and methods discussed herein which are not described in detail may be implemented in accordance with any conventional techniques for implementing such aspects and features. 
     Disc 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 termed antimicrobial susceptibility tests or testing (AST). The present disclosure proposes the use of an alternative procedure for this and other purposes using impedance flow cytometry. This technique uses apparatus to measure electrical properties, specifically a frequency dependent impedance, of individual particles flowing in a microfluidic channel. It has been found that exposure to antimicrobial agents (antimicrobials, antibiotics) can alter the impedance characteristics of a suspension of microorganisms (such as bacteria). The use of impedance flow cytometry to detect a change in the impedance of single microorganisms flowing through a microfluidic channel is proposed for the determination of susceptibility of the microorganisms to an antimicrobial agent or a combination of antimicrobial agents under test. The methods described herein can provide data on susceptibility of the microorganism being tested rapidly (for example within 30 minutes, within an hour or within 2 hours). The results give the same information on the ability of an antimicrobial to kill or prevent the growth of a microorganism as the gold standard tests being used currently, allowing conclusions to be reached about treatment options faster. The results provide more information regarding the mechanism and speed of action of the antimicrobial and population characteristics which may allow resistance prediction. ‘Gold standard’ tests include routine culture based methods which take a minimum of 6-8 hours for automated both microbiology and more usually from 16-20 hours from initial culture for the development of colonies/plaques on plates, or may be 48-72 hours for slow growing bacteria. Since each measurement reflects the characteristics of a single microorganism, the limits of detection are improved over existing tests. The improved time to result for the methods described herein offers advantages in tailoring antimicrobial therapy such as phage therapy for an individual patient and can help to ensure that antimicrobial agents such as phage are only used on susceptible clinical isolates. Bacteriophage provide alternative therapies for the treatment of multidrug resistant (MDR) infections, especially those cause 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 with a formulation comprising more than one phage (also known as a phage cocktail), for example targeting either isolates from the same species or a range of species. Time is particularly critical for patients suffering from MDR infections. The methods of the invention have the advantage that the susceptibility of a clinical isolate to an antimicrobial, such as phage, can be rapidly identified e.g. in less than or about 60 minutes, in about 15 minutes or in more than 15 minutes. 
     For the purposes of the present disclosure, an antimicrobial or antimicrobial agent is considered to be any agent that kills or inhibits growth of one or more strains of microorganism. 
     Examples of antimicrobials are antibiotics, antifungals and antivirals. Antibiotics are agents that kill (bactericidal) or inhibit growth (bacteriostatic) of bacteria. An antibiotic may act by one of a number of different mechanisms including, but not limited to, disrupting synthesis or integrity of the microbial cell wall, blocking protein translation, preventing nucleic acid replication, repair or maintenance within the cell, preventing synthesis of essential molecules (e.g. folic acid, cholesterol) and perturbing membrane structure. Examples of classes of antibiotics are Aminoglycosides, Ansamycins, Azoles, Carbacephems, Carbapenems, Cephalosporins, Echinocandins, Glycopeptides, Lincosamides, Lipopeptides, Macrolides, Monobactams, Nitrofurans, Oxazolidinones, Penicillins, Pleuromutilins Quinolones, Fluoroquinolones, Sulfonamides, Tetracyclines, Trimethoprim although other antibiotics and antimicrobials are not excluded. Cephlosporins, penicillins and carbapenems may be co-formulated with beta-lactamase inhibitors to improve efficacy. 
     Antimicrobials can exclude antibiotics, antifungals and antivirals. Antimicrobials can 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, Trimethoprim. Antimicrobials can exclude glycopeptides and lipopeptides. Antibacterials can include non-antibiotic agents. 
     Antimicrobials can include viruses such as bacteriophages (also known as phages). Viruses such as bacteriophages are more specific than antibiotics and may target one specific strain of microorganism e.g. bacterium. Thus antimicrobials can include more than one phage. More than one phage can be presented in the form of a panel of individual phage or a mixture of different phage (also known as phage cocktails). One or more phage can be tested. One or more cocktails of phage can be tested. Samples taken from recovering patients sometimes contain appropriate phages that can be used to cure other patients infected with the same strain. 
     Antimicrobials can include antimicrobial peptides such as anti-bacterial peptides, for example membrane penetrating, membrane disrupting or pore forming peptide antimicrobials. Antimicrobial peptides (sometimes referred to as host-defence peptides) can include bacteriocins, lanthipeptides, pyocins, phage-derived endolysins, endopeptidases, polymixins and muralytic proteins (e.g. Artilysins). It can also include synthetic antimicrobial peptides, based on repeated 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, which are typically 20-50 amino acids long, and can include pleurocidin and/or melittin. Linear antimicrobial peptides may be from 5, 10, 15 or 20 amino acids up to 50, 70, or 100 amino acids long. The peptides may consist of L-amino acids, D-amino acids, β-amino acids and combinations thereof. Cyclic peptides and peptides with derivatised or amino acids not routinely found in proteins, are also included. Antimicrobial peptides can exclude cyclic peptides and/or peptides with derivatised amino acids or amino acids not routinely found in proteins. Antimicrobials can include components of the innate immune system, including chemokines and host defense peptides, either whole or shortened derivatives of these molecules. Antimicrobials can include antibodies such as monoclonal antibodies, e.g. species-specific monoclonal antibodies. Antimicrobials can include serum from patients e.g. human patients, such as patients who may be infected with drug resistant bacteria or patient who are recovering from an infection by a microorganism. An antimicrobial agent can be one or more selected from the group of phage, a serum component, immune system components, and antimicrobial peptides, preferably where said antimicrobial peptides are membrane penetrating peptide, membrane disrupting peptide or pore forming peptide antimicrobials. An antimicrobial agent can be one or more selected from the group of phage, a serum component, immune system components, and antimicrobial peptides, and preferably where the antimicrobial peptides are linear antimicrobial peptides, membrane penetrating peptides, membrane disrupting peptides or pore forming peptides, and/or where the antimicrobial peptide consists of L-amino acids, D-amino acids, β-amino acids and combinations thereof, more preferably where the antimicrobial agent is not a glycopeptide or a lipopeptide. 
     For the purposes of the present disclosure, a microorganism is considered to be a microscopic organism, which may exist in its single-celled form or in a colony of cells. Examples of microorganisms include bacteria, virus and fungi (including yeasts and moulds). 
     Antimicrobials such as phages can be prepared for clinical use. A single antimicrobial can be used, such as a phage, for example Phage Ab_1, Phage Ab_2 or Phage Pa_1. A panel of antimicrobial agents can be used, such as a panel of phage, e.g. a set of phage known to target a specific causative agent associated with particular symptoms, such as urinary tract infection. Each antimicrobial agent, e.g. phage can be mixed with a separate sample of the one or more infectious agents. The panel of antimicrobial agents can be housed within a device containing multiple wells or channels, which can be interfaced directly with the impedance cytometer. Each antimicrobial agent can be mixed with each infectious agent and the susceptibility can measured by bacterial impedance flow cytometry, for example to generate a matrix of susceptibility. The data can be used to identify a combination of antimicrobials, e.g. phage, which can be used to treat a number of the infectious agents, such as multidrug-resistant isolates, at the same. Two or more phage (a ‘phage cocktail’) can be mixed with the same sample of infectious agent. Preferred phage include lytic phage, for example from the Myoviridae family and/or the Siphoviridae family. Antibiotic susceptibility and phage susceptibility impedance assays can be combined by mixing to identify synergistic combinations of phage and antibiotics which would be highly effective at treating the infection. Synergy between phage from any of the known phage families (including, but not limited to phage from the families Siphoviridae, Myoviridae, Podoviridae, Ackermannviridae, Inoviridae, Leviviridae, Microviridae, Cystoviridae) might be observed with any antibiotic (including, but not limited to, aminoglycosides, cephalosporins, penicillins, carbapenems, tetracyclines, (fluoro)quinolones, oxazolidinones, macrolides, lincomycins, glycopeptides, sulphonamides, pleuromutilins). Particularly preferred combinations include lytic phage and antibiotics that do not generally penetrate Gram-negative bacteria (e.g. rifampicin, novobiocin, vancomycin, linezolid, fosfomycin). 
     An infectious agent (microorganism) is identified. Identification can include isolation from a clinical sample. A clinical sample can include urine, blood and/or other sterile-site fluids, cerebrospinal fluid (CSFF), synovial fluid, or samples taken from wounds. The infectious agent may be assayed directly in a clinical sample. The clinical sample may undergo a treatment step, such as centrifugation, lysis of cells or filtration of cells, for example treatment to remove cells (such as red and/or white blood cells and/or platelets). The clinical sample may be plated out using standard microbiological techniques e.g. onto selective plates for specific organisms. Identification can include use of Maldi-Tof, or of one of more other bacterial ID systems. Bacterial ID systems include, EPI strips, automated bacterial ID platforms (e.g. Vitek systems, Biomerieux), traditional assay methods (Gram staining), metabolic tests (oxidase staining) and genotypic methods such as PCR with species specific primers. Identification could also include presumptive identification of the causative agent based on the symptoms of a patient, for example Enterobacteriaeae, such as  Escherichia coli, Klebsiella pneumoniae  and/or  Proteus mirabilis  in the case of a urinary tract infection. 
     The microorganism may be bacteria. A step may be used to isolate or subculture the bacteria from the sample, for example capture of bacteria on beads using physical-chemical or biochemical principles, such as poly cationic or poly anionic beads, beads coated with species-specific antibodies or generic bacteria capture ligands (e.g. mannose binding lectin, 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. A sample of the microorganism, for example bacteria, e.g. picked from a plate, is mixed with the phage. The mixture is incubated, e.g. for 10 minutes or more, 15 minutes or more, 20 minutes or more, about 30 minutes, about 45 minutes, up to 50 minutes, about an hour, 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 an hour. The sample is assessed on the impedance cytometer using any of the methods described herein. The sample is assessed on the 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, for example micro-organisms 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. for a population of bacteria. Incubation can take place on the impedance cytometer directly (e.g. to determine a time course) or in an incubator with automated sample loading onto the cytometer. A sample can be incubated outside the cytometer and assessed on the impedance cytometer at a fixed time (end-point determination). Preferred microorganisms include multiple drug resistant (MDR) bacteria, such as members of the ESKAPEE group ( Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, Enterobacter  spp or other members of the Enterobacteriaceae,  Escherichia coli ), drug resistant  Neisseria gonorrhoea, Stenotophomonas maltophilia , or  Burkholderia cepacia/cenocepacia  complex, more preferably  A baumannii  and/or  P. aeruginosa , for example one or more of:  A baumannii  strains NCTC 10303, NCTC13302, ATCC 17978, ATCC 17978 CoIR, and  P. aeruginosa  strain PAO1. 
     A control sample of untreated microorganism may also be assessed to generate reference data and a reference profile. Aspects of the profile of the microorganism indicative of susceptibility to the phage are assessed. Assessment can include comparison of the profile of the treated microorganism to a reference profile, including determination of the differences in profile. Assessment can be performed automatically using a software algorithm, using artificial intelligence and machine learning, or on the basis of simple scattergrams. The reference profile can be the profile of an untreated sample of the same organism. The reference profile can be the profile of the treated sample of microorganism at an earlier timepoint. The reference profile can be model profile, e.g. acquired previously from a sample of the same organism, or an average or standard profile for the organism, e.g. calculated from previously acquired data from multiple untreated samples or multiple treated samples. 
     A serial dilution of the phage may be used, in which a known number of phage (defined as plaque forming units) are mixed with a known number of bacteria and the profiles assessed. The lowest concentration of phage which is able to modify aspects of the profile of the microorganism indicative of susceptibility to the phage, allows the measurement of efficiency of infection (sometimes referred to as efficiency of plating), which help guide the number of phage which are required for therapeutics. This may be used in a similar way to an MIC determination, as used for antibiotics to determine the minimum concentration that prevents growth of the bacteria. A fixed concentration of phage to bacteria can also be used for testing, where the concentration is defined on the basis of the numbers of phage which might be delivered and maintained at a site of infection in a patient. This is akin to the clinical breakpoint threshold used for determining the resistance or susceptibility of the bacteria to an antibiotic. 
     Assessment can include determining the electrical opacity. The electrical opacity can be calculated from the impedance, e.g. |Z Highfrequency |/|Z lowfrequency |, for example where |Z Highfrequency | is measured at a frequency greater than 10 MHz and |Z lowfrequency| is measured at a frequency lower than  10 MHz, such as |Z 40 MHz |/|Z 5 MHz |. Assessment can include determining the electrical size. For example, the electrical radius can be calculated from the impedance, e.g. as |Z 1/3   5 MHz |. Assessment can include determining the phase. Assessment can include determining the proportion of cells that sit without a contour that encloses a percentage, for example 95%, of a control population, e.g. a population of normal untreated bacteria. Assessment can include determining the number and/or proportion of cells that sit within a contour that encloses a percentage, for example 95%, of a control population, e.g. a population of normal untreated bacteria. Assessment can include determining the number and/or proportion of cells that sit within a contour that encloses 50% of a control population. The contour can enclose 50%, 75%, 80%, 90% or 95% of the control population. 
     A bacterial impedance flow cytometry assay can be used to identify phage which can be used in narrow spectrum treatments for decolonization in chronic infections, such as the chronic diseases listed in Table 4, column 3, for example to target the pathogens listed in Table 4, column 1. 
     A method for performing serum bactericidal assays is provided. The impedance flow cytometry methods described herein can be used to assess the ability of serum, e.g. from a patient&#39;s blood, to kill a microorganism which is a pathogen of interest. The methods can assess e.g. levels of antibody or other components in the serum which can kill a microorganism. Other components could include antibiotics circulating in the blood or phage, for example in a patient that has recovered. The antibodies may be naturally occurring antibodies, or generated as a result of active or passive immunisation. The assay can be used to assess a combination of serum killing with one or more other antimicrobials, including but not limited to antibiotics and/or phage. A sample of the microorganism, for example bacteria, e.g. picked from a plate, optionally after incubation to increase the concentration of the microorganism and/or dilution e.g. to achieve a particular concentration of microorganism, such as 5.5×10 5  colony forming units (CFU) per mL is mixed with the serum, or a mixture comprising serum and one or more antimicrobial agents such as antibiotics and/or phage. The mixture is incubated, e.g. for 10 minutes or more, for 15 minutes or more, for 20 minutes or more, up to 50 minutes, or preferably for an hour. The sample is assessed on the impedance cytometer using any of the bacterial impedance flow cytometry methods described herein. A reference or control sample of untreated microorganism or of treated microorganism early in the timecourse, e.g. within 10 minutes of mixing the microorganism with the antimicrobial agent, may also be assessed to generate reference data and a reference profile. Aspects of the profile of the microorganism indicative of susceptibility to the antimicrobial peptide are assessed. 
     A method is provided for determining the efficacy of antimicrobial peptides using impedance flow cytometry. A sample of the microorganism, for example bacteria, e.g. picked from a plate, optionally after incubation, to increase the concentration of the microorganism, is mixed with the antimicrobial peptide(s). The mixture is incubated, e.g. for 20 minutes or more, for 30 minutes, for up to 50 minutes, or preferably for an hour. The sample is assessed on the impedance cytometer using any of the methods described herein. A control sample of untreated microorganism may also be assessed to generate control data and a control profile. Aspects of the profile of the microorganism indicative of susceptibility to the antimicrobial peptide are assessed. The profile of the antimicrobial peptide efficacy, can be used in combination with an antibiotic susceptibility test to determine synergistic interactions. This may be particularly relevant where the antibiotic is not usually able to get into Gram-negative bacteria and where the combination with the antimicrobial peptide, a membrane penetrating peptide, overcomes this barrier to entry. Particularly effective combinations would include, cationic antimicrobial peptides or other membrane penetrating peptides used with an antibiotic selected from a list that includes rifampicin, linezolid, fosfomycin, novobiocin, vancomycin. 
       FIG.  1    shows a simplified schematic cross-sectional side view of a first example of an apparatus for impedance flow cytometry, having a relatively simple format. The 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 required structures. The field of microfluidics is concerned with the behaviour, control and manipulation of fluids which are confined or constrained on a small scale, typically sub-millimetre, in other words on the micro-millimetre or smaller scale. Microfluidic devices constructed from layers on a substrate for the purpose of sample testing, in the biological and medical fields as well as other areas of endeavour, are sometimes referred to as “lab-on-a-chip”devices. In the  FIG.  1    example, the device  10  comprises a microfluidic flow channel  12  formed within a layer  14  of photoresist material, such as SU8, an epoxy-based negative photoresist, which is sandwiched between a lower layer  16   a  and an upper layer  16   b  of a glass material. Apertures in the upper glass layer  16   a  define an inlet  18  to the channel  12  and an outlet  20  from the channel  12 . A fluid sample  22  can be delivered into the channel  12  at the inlet  18  for flow along the channel  12  (indicated by dotted arrows in  FIG.  1   ) to the outlet  20  where it is removed or expelled as a waste product  24  or collected for further analysis. The sample  22  can be provided into the channel  12  by any convenient method, such as injection into the inlet  18  from a syringe  26 . A sheath flow may or may not be used to centre particles within the bore or orifice of the channel. Other mechanisms may be used to focus particles in the flow such as dielectrophoresis, acoustic, inertial or viscoelastic techniques. 
     The sample  22  comprises particles, which may be cells, bacteria, microorganisms or other biological particles (such as algae, exosomes, viruses or vesicles) or non-biological particles (such as droplets, beads, colloids, dust or metal fragments), depending on the nature of the testing being carried out, suspended in an electrolyte (electrolytic fluid). For AST, the particles are microorganisms which have or have not been exposed to an antimicrobial agent. To accommodate the passage of cells, the channel may have a cross-section in the direction transverse to the flow direction (from inlet to outlet) measuring around 40 μm high and around 40 μm wide. More generally, channel dimensions might be in the range of 1 to 100 μm. The cross-section may or may not be square. 
     The device  10  further comprises a first and a second pair of electrodes fabricated on the bottom and top walls of the channel  12 . Each pair of electrodes comprises 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 , but these positions may be reversed. The first electrode pair is located at an upstream position in the channel  12 , and the second electrode pair is located at a downstream position, so that particles in sample flow past the first electrode pair before the second electrode pair. The electrodes may have dimensions of the order 1 to 100 μm, such as 10 to 40 μm for analysing microorganisms and bacteria, although larger or smaller sizes are also possible depending on the channel size. 
     The voltage electrodes  30  are driven with a single voltage source  34  that may generate one or more frequency components f 1 , f 2 , f 3  . . . . Hence, both voltage electrodes  30  provide the same voltage, approximately equal in magnitude, frequency and phase. The two electrodes  30 ,  32  in 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 electrolytic fluid of a sample  22  flowing in the flow channel  12 . Current flowing in these current paths is detected at the measurement electrodes  32 . Current I 1  detected at the first measurement electrode and current I 2  detected at the second measurement electrode are each passed to a separate current-to-voltage converter  34 . The outputs of converters are passed to a differential amplifier  36  to obtain a differential signal representing the difference between the currents in the two current paths, namely I 2 −I 1  (or I 1 −I 2  if preferred). Further electronics (circuitry, a lock-in amplifier  38 , a processor  40 , for example), receive the differential signal and determine from it a measurement of impedance. This output or impedance signal may separate the impedance measurements according to the real (Re) and Imaginary (Im) components, or the components of magnitude |Z| and phase θ, as preferred. Particles passing between the electrodes of an electrode pair will alter the current detected at the measurement electrode, which is reflected in the final impedance signal. Hence, the presence of a particle, and characteristics of the particle, may be deduced from the impedance signal. 
     The inclusion of two pairs of electrodes gives two measurable currents and enables the differential mode of operation noted above, to reduce noise and artefacts. The purpose of the differential signal can be understood with reference to  FIGS.  2  and  3   . 
       FIG.  2    shows a schematic enlarged view of part of the device of  FIG.  1   , including the two electrode pairs, arranged across the flow channel  12 . A particle  42 , which will be a microorganism in an AST procedure, is suspended in fluid flowing along the channel  12 .  FIG.  3    shows graphs of the detected current over time during an impedance measurement.  FIG.  3 ( a )  shows the current I 1  detected by the first measurement electrode  32   a .  FIG.  3 ( b )  shows the current I 2  detected by the second measurement electrode  32   b .  FIG.  3 ( c )  shows the differential signal obtained from the differential amplifier (or other circuitry able to determine a difference signal), representing the difference between the two currents, I 2 −I 1 . 
     At a time t 0 , the particle  42  is in the channel but yet to encounter the electrodes. Both measurement electrodes  32   a ,  32   b  therefore detect substantially the same, non-zero, current since the same voltage (nominally) is supplied to both current paths. Therefore, the differential signal is substantially zero. At a later time t 1 , the particle  42  passes between the electrodes  30   a ,  32   a  of the first electrode pair. It impedes current flow in the first current path, and the detected I 1  is reduced, as shown in  FIG.  3 ( a ) . The second current I 2  is largely unaffected by the particle  42 . Therefore, the differential signal I 2 −I 1  becomes positive as the particle  42  passes the first electrode pair  30   a ,  32   a , as shown in  FIG.  3 ( c ) . Then at time t 2 , the particle is at an intermediate point after the first electrode pair  30   a ,  32   a  and before the second electrode pair  30   b ,  32   b , so both currents are again approximately equal and the differential signal returns to zero. At time t 3 , the particle  42  reaches the second electrode pair  30   b ,  32   b , and impedes the current flow in the second current path. Hence, at t 3 , the first current I 1  has its full value (see  FIG.  3 ( a ) ), the second current I 2  has a reduced value (see  FIG.  3 ( b ) , and the differential signal becomes negative (see  FIG.  3 ( c ) ). At time t 4 , 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 differential signal can be carried out to deduce the impedance of the particle. The size, structure, shape and composition of the particle determine its impedance properties and hence the effect it has on the current in the current paths defined by the electrode pairs, and on the differential signal. Exposure of a microorganism to an antimicrobial agent to which the microorganism is susceptible will modify the size, structure, shape and/or composition of the microorganism, so that its impedance properties are altered. This is reflected in the differential signal. Accordingly, comparison of the differential signal, or the impedance signal derived from the differential signal, from a sample of microorganisms that has been exposed to an antimicrobial agent to that from a sample of microorganisms that has not been exposed to the antimicrobial agent can indicate whether the microorganisms have any susceptibility to that agent. Hence, AST can be achieved using impedance flow cytometry. Certain cell properties that are modified by antimicrobial treatment show a frequency-dependent response, so utilisation of a voltage with appropriate single or multiple frequency components and processing of the differential signal to extract the impedance response at different frequencies can reveal additional information about susceptibility. Impedance flow cytometry offers advantages over other techniques for AST. For example, it is much faster than disc diffusion and broth microdilution AST and does not require a priori knowledge of the microorganism. Further, the method does not require the addition of costly dyes that are frequently used for optical cytometry, nor are any washing steps needed after exposing the microorganisms to antimicrobials, so impedance flow cytometry can be cheaper and faster than other techniques for AST. It can also be performed in the presence of the antimicrobial agent so that time-dependent changes can be determined. 
     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 the electrodes, and the applied voltage signal. However, the change in the current produced by a passing particle of the size of a microorganism or bacteria cell (which is smaller than a mammalian cell) is in the range of about 1 μA to 1 nA, i.e. between about a thousand to a million times smaller (note that the current plots in  FIGS.  3 ( a ) to ( c )  are not to scale). The differential signal therefore has a small magnitude and is relatively susceptible to noise. In order to maximise the signal-to-noise ratio of the differential signal, the voltage applied to the voltage electrodes can be as high as possible and the gain in the current-to-voltage converters can be maximised. However, as the applied voltage is increased, each of I 1  and I 2  are increased proportionally, and this leads to clipping in the current to voltage converters and the differential amplifier. Overall, the non-zero currents limit the maximum voltage and gain which can be used, which in turn limits the sensitivity of the device. Another approach for measuring microorganisms with impedance flow cytometry is to reduce the channel size so as to shorten the current paths between the electrodes, so that the small-sized microorganisms have a proportionally greater impact on the detected current (since the size of the microorganisms relative to the channel size is greater). However, narrower channels are prone to blockages, and also increase the backpressure in the channel since this scales with the fourth power of channel size. 
     Accordingly, an impedance flow cytometer such as the  FIG.  1    example has some limitations when measuring particles of a small size, such as microorganisms and bacterial samples for the purpose of AST. Nevertheless, useful AST data can be obtained. The microfluidic flow past electrodes allows detection and measurement of individual microorganisms, so that microorganism counting can be achieved, and data for individual particles within a population of microorganisms in a sample can be obtained and analysed for the total population. Various measurement techniques for AST are described in more detail below with respect to other example impedance flow cytometers; these can also be carried out with apparatus such as that in  FIG.  1   , or other impedance flow cytometry apparatus. 
     The present disclosure describes examples of an alternative design for an impedance flow cytometer that can offer improved sensitivity and performance. It can be used in methods to accurately measure samples comprising small particles such as bacteria and/or cells, (or indeed any biological or non-biological particles) in large diameter channels (although smaller channel sizes are not excluded). The device comprises electrodes disposed to create current paths through a microfluidic channel, where the electrodes are configured and driven to provide an improved measurement sensitivity. Hence, impedance flow cytometry can be used for AST and other measurements, tests and assays on bacterial particles, and other biological and non-biological particles. The apparatus has much wider application, however, and can be used to obtain impedance information about any type of particle that can be suspended in an electrolyte fluid for flow in a channel past appropriately configured electrodes. 
       FIG.  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  FIG.  1   , although other structures and configurations may be used instead. The channel  12  has, in this example, a total of eight associated electrodes. Each electrode is on an inner surface of a flow channel  12  so that it is contact with sample fluid flowing in the flow channel  12 . Alternatively the electrodes could be thinly separated from the electrolytic sample fluid. 
     The electrodes are configured as a first electrode group  50  and a second electrode group  52 . The electrodes are configured as either signal electrodes for applying an electrical signal (current or voltage) or measurement electrodes, arranged in pairs to provide current paths through fluid flowing in the channel  12 . Each of the first electrode group  50  and the second electrode group  52  provides a first current path from a signal electrode to a measurement electrode, and a second current path from a different signal electrode to a measurement electrode. In the present example, each of these electrodes is separate element. Hence, each electrode group comprises four electrodes, and the device comprises a total of eight electrodes. The first electrode group  50  comprises a first signal electrode  60   a  above the channel  12  that makes a first current path I 3  with a first measurement electrode  62   a  below the channel  12 , and a second signal electrode  64   a  above the channel  12  that makes a second current path I 4  with a second measurement electrode  66   a  below the channel  12 . The second electrode group  52  comprises a further first signal electrode  60   b  above the channel  12  that makes a further first current path I 6  with a further first measurement electrode  62   b  below the channel  12 , and a further second signal electrode  64   b  above the channel  12  that makes a further second current path I 7  with a further second measurement electrode  66   b  below the channel  12 . In this example, the electrodes are arranged in pairs along the flow channel length, so 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. 
     Within the first electrode group  50 , the first signal electrode  60   a  is driven with a first voltage +V, which has a specified magnitude, phase and frequency composition (one or more frequencies). In contrast, the second signal electrode  64   a  is driven with a second voltage −V which has the same magnitude and frequency composition as the first voltage +V, but which is 180° (π radians) out of phase with the first voltage. 
     The signal electrodes of the second electrode group  52  are driven with the same voltages as the corresponding signal electrodes of the first electrode group  50 . Hence, the further first signal electrode  60   b  is driven with +V and the further second signal electrode is driven with −V, where the magnitudes and frequencies are identical with the first and second voltages of the first electrode group  50 . In the  FIG.  4    example, this is achieved by supplying the first signal electrode  60   a  and the further first signal electrode  60   b  from a first voltage source  70  producing +V, and supplying the second signal electrode  64   a  and the further second signal electrode  64   b  from a separate second voltage source  72  producing −V. 
     Note that it is not essential that the magnitude and frequencies are absolutely identical, and in real-world conditions it is likely that some small differences will occur. Hence, terms such as “same” and “identical” in this context are not limiting, and are intended to include arrangements in which the voltage characteristics are similar or approximately, substantially or nominally the same, for example within boundaries which the skilled person will understand as being acceptable for achieving a meaningful output signal as described herein. 
     Similarly, a phase difference of precisely 180° is not essential, and the phases may differ by other amounts in the region of 180°. Accordingly, the phases of the two voltages may be considered to be “opposite”, where this is intended to include arrangements in which the phase difference is close to or approximately, substantially or nominally 180° (π radians), within boundaries which the skilled person will understand as being acceptable for achieving a meaningful output signal as described herein. 
     In this example, the signal electrodes are driven at specified voltages from voltage sources, so might be considered to be voltage electrodes. In other examples, the signal electrodes may be driven at specified currents from current sources. Accordingly, the term “signal electrode” is intended to include both alternatives, such that these electrodes provide electrical signals with a frequency, magnitude and phase difference as described and which may be a voltage signal or a current signal. In any of the various examples, voltage sources and voltage electrodes may be substituted with current sources and current electrodes, or vice versa. Similarly, the application of a voltage may more generally be understood as the application of an “electrical signal”, which may be a voltage or a current depending on the choice of electrical source. 
     The measurement electrodes are configured with circuitry that produces a differential signal indicating the difference between measurements from the first electrode group  50  and the second electrode group  52 . As shown in  FIG.  4   , this is implemented in the present example by summing or combining the current I 3  detected in the first current path (by the first measurement electrode  62   a ) with the current I 4  detected in the second current path (by the second measurement electrode  66   a ), to produce a summed signal I 5 . This first summed signal I 5 , from the first electrode group, is passed to a current-to-voltage converter  34   a . Similarly, the current I 6  detected in the further first current path (by the further first measurement electrode  62   b ) is summed or combined with the current I 7  detected in the further second current path (by the further second measurement electrode  66   b ) to produce a summed signal I 8 . This second summed signal I 8 , from the second electrode group, is passed to another current-to-voltage converter  34   b . Note that in an alternative arrangement, the circuitry could be configured to implement the current-to-voltage conversions before the summing or combining. In either case, the first summed signal I 5 , representing the sum of current flow in the first and second current paths of the first electrode group  50 , and the second summed signal I 8 , representing the sum of current flow in the first and second current paths of the second electrode group  52 , are passed to further circuitry configured to determine a differential signal that represents the difference between the first summed signal and the second summed signal. In the  FIG.  4    example, this comprises a differential amplifier  36 . Then, the differential signal can be processed using appropriate processing circuitry or electronics, to calculate from the differential signal an impedance signal indicating 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, effects of an antimicrobial agent on microorganisms in the sample fluid can be identified by comparison with measurements of impedance from samples of the same microorganisms not treated with antimicrobial agents, or treated with different types or amounts of antimicrobial agent. For example, the differential signal may be inputted to a processor configured to process the differential signal for the purpose of determining impedance signals, impedance values, impedance properties and characteristics of fluid and/or cells, and/or cell counts, as described herein and further below. The circuitry and processing can be implemented with any suitable configuration or combination of hardware, firmware and software, including simple electrical connections, logic gates, amplifiers and central processing units. A single processor or similar processing electronics or circuitry can be used to handle multiple differential signals, for example obtained from multiple flow channels with associated electrodes that may be implemented on a single substrate or chip. An apparatus configured in this way enables simultaneous measurements to be obtained simply for multiple samples. In the context of microorganism testing, this can allow a reference sample of untreated microorganisms to be measured at the same time as a treated sample, or multiple samples of a particular microorganism to be tested with different antimicrobial agents, or multiple samples of a particular microorganism to be tested with different concentrations of the same antimicrobial agent to determine the so-called minimum inhibitory concentration. Derivation of the differential signal can be understood from  FIG.  5   , which shows graphs of current against time for the two summed signals (a) and (b), and the corresponding differential signal (c). 
       FIG.  4    shows a particle  42 , such as a bacterial cell, in the flow channel  12  at a position in which it is upstream of the first electrode group  50 , and about to enter a measurement region defined by the electrodes. By time t 5 , the particle  42  has passed all the electrodes and exited the measurement region. The graphs in  FIG.  5    show the various signals at t 0  and subsequent times t 1  to t 4  before t 5 . For convenience and simplicity, the fluid sample may have a cell concentration and a flow speed along the fluid channel that is intended to provide only one particle at a time in the measurement region, being the zone within which the electric fields of the electrodes are present. 
     At t 0 , the particle  42  is outside the measurement region, and does not interact with any of the current paths. Hence, in the first electrode group  50 , the first measurement electrode  62   a  detects a current I 3  in the first current path which is the same magnitude but opposite phase to the current I 4  in the second current path detected by the second measurement electrode  66   a . Therefore, I 3  and I 4  cancel one another out, and their sum is zero (or approximately zero, given any minor differences in the electrical signals delivered by the signal electrodes), giving a first summed signal I 5  of zero at t 0 , as in  FIG.  5 ( a ) . Similarly, in the second electrode group  52  the current I 6  at the further first measurement electrode  62   b  is equal but opposite to the current I 7  at the further second measurement electrode  66   b , so that their sum is also approximately zero, giving a second summed signal I 8  of zero, shown in  FIG.  5 ( b ) . Therefore, at t 0 , the differential signal I 8 -I 5  is also zero, as shown in  FIG.  5 ( c ) . Hence, the “background” signal measured by the apparatus, when no particle is present, is substantially zero-valued and obtained from the difference of two zero-valued measurements. Accordingly, the voltages applied at the voltage electrodes can be raised to a high value without the detected signals undergoing any clipping in the converters  34  or the differential amplifier  36 , so the measurement sensitivity can be maximised within the capability of the voltage sources. 
     At time t 1 , the particle is between the first signal electrode  60   a  and the first measurement electrode  62   a , so impedes the current flow in the first current path. I 3  is therefore reduced. The current flow I 4  in the second current path, between the second signal electrode  64   a  and the second measurement electrode  66   a , remains as before. The first summed signal I 5 , being I 3 +I 4 , is therefore also reduced. The second summed signal I 8 , being I 6 +I 7  from the second electrode group, remains at approximately zero, since no particle is in either of these current paths. The differential signal I 8 −I 5  therefore becomes positive, owing to the reduced value of I 5 . At t 2 , the particle  42  has moved to be between the second signal electrode  64   a  and the second measurement electrode  66   a . The current I 3  in the first current path resumes its previous value, and the current I 4  in the second current path is reduced, by the presence of the particle  42 . Recall that the second signal electrode has a negative driving voltage, however, so that the first summed signal I 5 =I 3 +I 4  becomes positive, as shown in  FIG.  5 ( a ) . The second summed signal I 8  remains at approximately zero. Accordingly, the differential signal I 8 −I 5  becomes negative at t 2 . 
     At time t 3  and then later at time t 4 , the particle enters the second electrode group  52 , and interacts with the further first current path I 6  at t 3 , and then the further second current path I 7  at t 4 . Since the further first current path I 6  has the same voltage supply as the first current path I 2 , and the further second current path I 7  has the same voltage supply as the second current path I 4 , the second summed signal follows the same shape at times t 3  and t 4  as the first summed signal showed at times t 1  and t 2 , becoming negative in t 3  and positive in t 4 . Meanwhile, the first summed signal I 5  remains zero during these times since no particle is present in the part of the measurement region corresponding to the first electrode group. Hence, in t 3 , the differential signal I 8 −I 5  goes negative, and then becomes positive in t 4 , as shown in  FIG.  5 ( c ) . 
     At t 5 , the particle has left the measurement region, so all four current paths are unperturbed. Both summed signals will be substantially zero, giving a zero-valued differential signal, as at time to. 
     Note the particular shape of the curve followed by the differential signal, shown in  FIG.  5 ( c ) . The sequential arrangement along the channel length of the two electrode groups  50 ,  52  and the four pairs of electrodes with the groups, together with the alternating arrangement of positive and negative voltages for the signal electrodes along the channel length, gives a corresponding differential signal that shows positive then negative then negative than positive features over time, as a particle passes along the measurement region. This shape is more distinct compared to noise than the differential signal from the  FIG.  1    apparatus, so can be more readily distinguished (using signal processing techniques). This enhances the signal to noise ratio, further improving the sensitivity. 
     The differential signal may alternatively be calculated as I 5 −I 8 , if preferred, 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 properties of the particle can be determined from it. This is also applicable to examples described further below. 
     This electrode configuration (and similar configurations enabling the same result) and its improved performance enables meaningful impedance measurements to be obtained for small particles such as bacteria flowing in a large channel. This reduces the risk of blockages of the channel, and makes such an apparatus more usable in real-world environments and situations. Bacterial cells typically range in size from 0.2 to 2 μm. By “a large channel”, it is meant that the dimensions of the channel in the plane transverse to the fluid flow direction are in the range of about 10 to 50 μm, such as 20 μm. As an example, the channel may have a square cross-section (arising for example from the layered construction and formation with photolithography) with a substantially equal width and height of about 40 μm. Alternatively, the channel may have a height, being a dimension orthogonal to a plane of the substrate on which the apparatus is formed and to the direction of flow, and parallel to the current flow path from a voltage electrode to a measurement electrode, of about 10 to 50 μm, such as about 20 μm, with the transverse (width) dimension, being larger. Other dimensions may also be used, such as a channel with a smaller dimension in the range of 100 to 1000 μm suitable for measuring cells about 10 μm across, or still larger channels able to accommodate particles on the millimetre scale. 
     Other electrode configurations may be used to obtain the same or similar signals from which impedance characteristics of particles in the sample fluid may be deduced. A variety of arrangements comprising a first electrode group and a second electrode group each providing a first current path and a second current path driven at approximately equal but approximately opposite voltages is possible. Within a group, the first current path and the second current path may be at different locations along the flow direction of the channel, as in  FIG.  4   . The first electrode group and the second electrode group may also be at different locations along the flow direction of the channel, also as in  FIG.  4   . The electrodes of each group need not be physically grouped together, however, and may be dispersed among electrodes of the other group. 
       FIG.  6    shows a second example, in a schematic cross-sectional side view including the same elements as  FIG.  4   . Hence, eight electrodes are included, comprising four signal electrodes and four measurement electrodes disposed as four pairs across the flow channel  12 . However, in this example, the signal electrodes of each electrode group are alternated along the flow channel. Thus, in order along the flow channel  12 , the measurement region comprises firstly the first signal electrode  60   a  and its first measurement electrode  62   a  to give the first current path I 3 , secondly the further first signal electrode  60   b  and its further first measurement electrode  62   b  to give the further first current path I 6 , thirdly the further second signal electrode  64   b  and its further second measurement electrode  66   b  to give the further second current path I 7 , and lastly the second signal electrode  64   a  and its second measurement electrode  66   a  to give the second current path I 4 . The first current path I 3  and the second current path I 4  are combined for the first summed signal I 5 , and the further first current path I 6  and the further second current path I 7  are combined for the second summed signal I 8 , as before. The time evolution of the differential signal for a particle traversing the measurement region will be differently shaped from that shown in  FIG.  5 ( c ) —it will comprise positive then negative then positive then negative features—but can be distinguished from noise by appropriate filtering and/or signal processing. 
     The examples of  FIGS.  4  and  6    both comprise separate voltage sources (or current sources) to supply the first electrical signal to the first signal electrodes in each group and the opposite second electrical signal to the second signal electrodes in each group. The signal electrodes are connected to one side of the voltage source, and the other side is connected to ground. 
       FIG.  7    shows a schematic cross-sectional side view of an alternative example that is simplified by use of a single voltage source to drive all the signal electrodes. This example comprises eight electrodes, positioned the same as in the  FIG.  6    example. A single voltage source  71  drives all the signal electrodes. The first signal electrodes  60   a ,  60   b  of each electrode group are connected to the positive side of the voltage source  71  to receive +V, and the second signal electrodes  64   a ,  64   b  of each electrode group are connected to the negative side of the voltage source  71  to receive −V. 
     As has been noted, the apparatus may be driven using voltages or currents applied to the signal electrodes.  FIG.  8    shows an example apparatus configured as the  FIG.  4    example, but using current sources in place of voltage sources. Components are otherwise the same so are not described in detail here. A first current source  80  provides a current with a magnitude, phase and frequency composition to the first signal electrodes  60   a ,  60   b  of each of the first and second electrode groups  50 ,  52 . A second current source  82  provides a current with substantially the same magnitude and phase to the second signal electrodes  64   a ,  64   b  of each electrode group  50 ,  52 , but which is negative compared to the current from the first current source  80  in that it has an opposite or approximately opposite phase (the phase difference between the two currents is about 180° or π radians). Voltages V 1  and V 2  representing the summed signals from the measurement electrodes  62   a ,  66   a ,  62   b ,  66   b  of each electrode group  50 ,  52  are input to a differential amplifier  36  to allow the differential signal to be determined. 
     Other configurations for the electrodes and the resultant current paths are also possible. Typically, the electrodes will be above and below the flow channel owing to the constraints of conventional fabrication of a layered microfluidic structure, but this is not essential for operation, and the apparatus may be configured with electrodes disposed about the channel in other orientations. In an example, the positive and negative signal electrodes may be placed adjacently as in the  FIG.  6    example, but with measurement electrodes of the first group placed as the two central measurement electrodes and measurement electrodes of the second group placed as the two outer measurement electrodes, opposite to the  FIG.  6    arrangement. The examples so far have all comprised signal electrodes at the top of the flow channel and measurement electrodes at the bottom of the channel. This is not a limitation, however, and any of the electrodes may be placed in either position, perhaps according to convenience in connecting them with the voltage or current source(s) (electrical signal sources) and the measurement circuitry. For example, the electrodes of one or more pairs of signal electrode and measurement electrode may be oppositely arranged so that the measurement electrode is above the channel and the signal electrode is below the channel. Further, the individual electrodes may be combined in larger electrodes that perform the function of two individual electrodes, for example where those electrodes are physically adjacent. Considering the  FIG.  4    example, the first measurement electrode and the second measurement electrode, in the first electrode group, are adjacent, and the further first measurement electrode and the further second measurement electrode, 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 single combined electrode that collects the current from both the first current path and the second current path, so that its output is already a combined or summed signal from the first electrode group. Similarly, the further first measurement electrode and the further second measurement electrode can be replaced by a single combined electrode that outputs the 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 an electrode group as described thus far, the signal electrodes comprise two electrodes that apply different, opposite electrical signals (voltage or current) to the two current paths of that group. Therefore, the signal electrodes within a group cannot be combined. However, the same voltages or currents (nominally) are applied to corresponding positive and negative signal electrodes in the two different electrode groups, giving scope for signal electrodes to be combined or shared across the electrode groups. Thus far, the examples have comprised electrodes paired to provide current paths that pass through the fluid channel in a direction roughly transverse to the fluid flow direction; this is achieved by the paired electrodes being disposed on opposite sides of the channel. This is not essential however, and the current paths may be otherwise situated, in any arrangement that allows suspended particles to interact with the electric fields emanating from the voltage electrodes and hence modify the current flow in the current paths. For example, the electrodes can be arranged so that signal electrodes and measurement electrodes alternate along the upper and lower sides of the channel, but are arranged opposite to a same type of electrode. Hence, the signal electrodes producing the same electrical signal are opposite to one another, and the electric fields are directed along the direction of the channel length to the adjacent measurement electrodes. Such an arrangement provides current paths which are substantially along, or parallel to, the fluid flow direction through the channel. The electrodes may be planar, which is convenient in a chip-based device fabricated in layers, but this is not essential. For example, the electrodes may be formed as rings or collars sequentially surrounding the channel, which might be of circular or oval cross-section, formed from a pipe or tube, for example. 
     In further examples, the number of electrodes may be increased, to provide additional current paths. This will increase the distinctive nature of the pattern of the differential signal, making it easier to isolate from noise and hence improving the sensitivity. The number of electrode groups is maintained as two, and within each group, extra electrodes provide additional first and second current paths. The particle impedance signal can be extracted from height-related features of peaks and troughs in the summed signal and/or the differential signal. This can be accomplished by measuring the amplitude of the peaks and/or troughs, or matching the shape of the signal to templates obtained for particles with known characteristics, for example. The sequence of the peaks and troughs in the summed signals and/or the final differential signal can be designed by choosing the relative sequence of the signal electrodes. It is known from signal processing mathematics that some signal shapes are more unique than others, so that an improved signal to noise ratio can be obtained by an appropriate sequence of the electrodes along the flow channel. 
     As discussed, the various described examples of impedance flow cytometry apparatus are applicable to measurements of bacteria and microorganism samples, such as AST, where the examples of  FIGS.  4  to  8    are particularly beneficial for this purpose compared to the example of  FIGS.  1  to  3    because they can process small sized particles with measurement sensitivity sufficient to obtain meaningful data. Thus, the presently disclosed impedance flow cytometers and their use have application for improved diagnosis of microbial infection and prescription of antimicrobial agents. Furthermore, in the examples of  FIGS.  4  to  8    the flow channel of the apparatus is able to have significantly larger dimensions than typical bacterial cell sizes, so apparatus of this type is also useful for measurements of samples of non-bacterial cells, which typically have a larger size than bacterial cells, or for mixed samples containing a range of particle sizes, and indeed for particles of non-biological origin. 
     Various example measurement techniques and procedures that can be implemented using impedance flow cytometry will now be described. The descriptions are made with reference to apparatus such as the  FIGS.  4  to  8    examples, but in general, these and similar methods may also be implemented using an apparatus such as the  FIGS.  1  to  3    example. 
     The differential signal generated by the impedance flow cytometry apparatus has a particular shape (the exact details of which depend on the ordering of the various electrodes, which can be selected to increase the distinctiveness of the signal shape or pattern), so at a simple level, the apparatus may be used for particle or cell counting. The processing of the differential signal may comprise a simple identification and count of all occurrences of the particular shape of the signal that arises from the passage of a particle through the measurement region. This can be used for counting of regular cells, but is also applicable to identification of biological susceptibility to antimicrobial agents. Some antimicrobial agents act by disrupting the structural integrity of the microorganisms, so that if a strain of microorganism is susceptible to an antimicrobial agent of this type, exposure of the sample to the antimicrobial agent will over time reduce the population of microorganisms in the sample. This can be identified by counting the number of treated microorganisms in an accurately volume-measured sample and comparing it to the count of a sample of untreated microorganisms at a specified time point or series of time points. Simple analysis of this type may not require any detailed calculation or analysis of the actual values of impedance of particles in the fluid sample; there may not be a need to derive an impedance signal from the differential signal, or to identify impedance values, properties or characteristics of the particles from the impedance signal. 
     However, analysis of the impedance signal can reveal additional valuable information about cells, and microbial susceptibility to antimicrobial agents in particular. Methods according to the present disclosure enable a range of impedance-based measurements to be made that can reveal information about biological and non-biological particles, including cells and bacteria, in a simple and rapid manner with a minimal number of steps. 
     Different classes of antimicrobial agents have different modes of operation, and produce different biophysical changes in microorganisms. As noted above, some antimicrobial agents disrupt the structural integrity of microorganisms, thereby reducing the population size, which can be detected via a particle count in an accurate sample volume. Other antimicrobial agents operate by inhibiting cell wall synthesis, which can produce an overall increase in cell volume (size). The cell wall or cell membrane properties themselves may be altered, such as a change in thickness, electrical or material properties, or porosity, and the internal cell structure or composition may change. These various characteristics—cell size, cell wall/membrane properties, internal properties—all contribute to the impedance properties or value of the cell. Accordingly, measurement of the impedance of particles in a sample can reveal characteristics of the cells. Comparison between measurements of samples of microorganisms treated and untreated with antimicrobial agents to identify any differences can reveal if the characteristics have been changed by the antimicrobial exposure, indicating a measurable susceptibility to the antimicrobial agent. Measurement of the impedance of particles in a sample can also reveal the mode of action of the antimicrobial agent giving rise to one or more characteristics, or a change in one or more characteristics. The antimicrobial agent can remain in the sample for the cytometry measurement, or may be removed by washing before the measurement if preferred. There is no need for removal, however, which is a beneficial aspect of the method herein compared to optical cytometry techniques, in which it is typically necessary to remove an antimicrobial agent from a sample before adding a necessary dye. To determine susceptibility, a threshold level for a change in one or more characteristics reflected in the impedance measurement can be set. If comparison between impedance signals from antimicrobial agent unexposed and exposed microorganism samples shows that the amount of change is at or above the threshold, susceptibility can be recognised. The threshold might be, for example, a threshold for a change in the measured size of a characteristic, or a threshold for the number of microorganisms in the sample exhibiting that change, for example. 
     On a simple level, the magnitude of the differential signal obtained using an apparatus as described herein, an example of which is shown in  FIG.  5 ( c ) , has a dependence on particle size. A larger particle has a greater effect on or interaction with the electric field in the flow channel, so the current flow is reduced more, and a lower current is detected at the measurement electrode. The differential signal will therefore contain peaks and troughs of a larger amplitude than for a smaller particle. Comparison of a measurement from exposed microorganisms with that from unexposed microorganisms may therefore reveal antimicrobial susceptibility if the differential signal from the former measurement shows larger amplitude features than the latter sample. One may consider the differential signal directly for this analysis, or calculate corresponding impedance values from the differential signal. 
     When considering impedance values, recall that impedance comprises two parts or components, the real part and the imaginary part, or more usefully, the magnitude |Z| and the phase θ. Any value or combination of these components may be analysed to investigate properties of particles in a sample fluid. Moreover, the nature of the interaction of a particle with the electric field depends on the frequency of the electric field. Hence, different impedance results can be obtained by measuring at different frequencies or more than one frequency, and these can reveal different characteristics of the particle. The measurement might be done by studying one sample of microorganism at one frequency and studying another sample of the same microorganism at a second frequency, by connecting a different voltage or current source to the signal electrodes or setting the signal source to output a different frequency to the signal electrodes. More conveniently, however, the signal source or sources used to drive the signal electrodes can be configured to output more than one frequency at the same time. Appropriate filtering and/or processing of the differential signal or the impedance signal derived from it can be carried out to isolate the different frequency components in the recorded measurements, so that one or more impedance components (e.g. magnitude and/or phase) can be obtained for each frequency component. 
       FIG.  9    shows representations of the interaction of a particle (cell) with electric fields of different frequencies. A cell  42  suspended in an electrolytic fluid is in an electric field (indicated by the lines), such as would be present in the flow channel between a signal electrode and a measurement electrode. In  FIG.  9 ( a ) , the frequency is low, by which is meant a frequency in the range of about 10 MHz or less, such as 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 into the cell and are diverted around it), and the measured impedance signal reflects the electric volume of the cell (representative of the cell&#39;s physical size). Accordingly, the cube root of the measured impedance magnitude, |Z| 1/3 , approximately reflects the electric radius. In  FIG.  9 ( b ) , the frequency is high, by which is meant a frequency greater than the low frequency, for example a frequency which is greater than about 10 MHz, such as 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 unperturbed). The effect of this 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&#39;s interior. This can be termed the “electric opacity”. Accordingly, differences in these characteristics between two cells will be apparent as differences between the measured impedances at a high frequency. Note that useful values for high and low frequencies will be different, or significantly different, from these example values for other cell types, other particle types, and/or different conductivities of the suspending electrolyte. For example, values for a high frequency of about 1 MHz for non-bacterial cells and about 10 MHz for bacterial cells in a suspending medium with a conductivity similar to physiological media might be suitable. A low frequency is one at which the electric field generally does not penetrate the particle, and from which size information about the particle can be deduced. A high frequency is one which is higher than a chosen low frequency, and at which the electric field couples across the cell wall, allowing properties dependent on the cell&#39;s membrane and wall to be investigated. At much higher frequencies (about 5 MHz or above for non-bacterial cells and about 50 MHz or above for bacteria, considered to be within a high frequency regime for the present disclosure), internal structure and component parts can be measured. 
     Hence, there is a distinction between measurements at different frequencies (particularly between low frequencies and high frequencies as defined above) of the same particle that depend on properties of that particle, from which information about those properties can be deduced. Other parameters also affect the distinction, including the conductivity and permittivity of the suspending electrolyte fluid, but this and other parameters which are features of the apparatus and the testing regime or protocol can be kept constant across multiple measurements so do not impact on comparative analyses. 
     Measurements may be obtained at a single frequency only, which may be high or low, or at more than one frequency, typically two, either sequentially or simultaneously. 
     An approach for two frequencies is, for an individual particle, to calculate the impedance (magnitude, phase, real or imaginary components) at the low frequency, and the impedance at the high frequency. These values are plotted on a graph, together with the values for other particles in the same sample, to produce a scatter plot. The low frequency impedance magnitude, indicating the electric radius or electric volume, may be plotted on the x-axis of the graph, and the high frequency impedance magnitude may be plotted on the y-axis of the graph. Alternatively, the y-axis may plot the ratio of the high frequency value to the low frequency value, thereby normalising the opacity to the cell size; this is termed “electrical opacity”. 
     In the figures presented herein, each point in the scatter plot (also referred to as scattergrams) has a colour which represents the number of particles, where black represents one particle as the number of particles increases the colour of the point becomes paler grey. Thus, a pale colour indicates a higher intensity (a large number of particles) and a darker colour indicates a lower intensity (smaller number of particles). 
       FIG.  10    shows four example scatter plots.  FIG.  10 ( a )  shows measurements for a bacterial strain that has not been treated with any antimicrobial. The measurements were obtained at two frequencies, a low frequency of 5 MHz and a high frequency of 40 MHz. The impedance value for each cell at the low frequency, |Z| 5 MHz , is plotted on the x-axis, and the normalised impedance value for each cell at the high frequency, |Z| 40 MHz /|Z| 5 MHz , is plotted on the y-axis. Each data point corresponds to an individual particle in the sample. For calibration/reference purposes, the sample included a quantity of plastic micro-beads, of a known size which may be broadly comparable to the bacteria size, and known dielectric properties (known impedance characteristics). The beads appear on the graph centred around a high frequency value of 1, and a low frequency value of 1.5, for single beads. Bead which become stuck together into doublet and triplet groups appear as smaller populations at higher low frequency values, to the right of the main bead population. However, all the beads are well-separated from the data points representing the bacterial cells in the sample. These are centred on a high frequency value of about 0.75, extending over a low frequency range of about 1.6 to 2.4. A closed solid line is superimposed over the bacteria data points to indicate the location of the bulk of the bacterial population. This line can be considered as a contour line or boundary, or a gate, and is useful for comparing measurements from different samples. It can be drawn to encompass all the data points of the bacteria, or a central proportion of the data points such as 99%, 95%, 90%, 75% or 50% so that outlying measurements are excluded. Known statistical techniques can be utilised to place and size the contour. 
       FIG.  10 ( b )  shows measurements for a sample of the same bacterial strain which has been incubated with an antimicrobial agent, in this example, from an antimicrobial class called β-lactams, for 30 minutes. The data points for the beads are unchanged from  FIG.  10 ( a ) , since the antimicrobial has no effect on the plastic material. The data for the bacteria, however, have shifted significantly to higher impedance values at the low frequency, now occupying a range of about 2.1 to 3, and shifted somewhat to lower impedance values at the high frequency, now centred at about 0.7. The solid contour line from  FIG.  10 ( a )  is reproduced in  FIG.  10 ( b ) . Almost no data points lie within the solid line, indicating that virtually the entire population of bacteria has been substantially modified by the antimicrobial agent. The shift to larger low frequency values indicates an increased electric radius, and the shift to smaller high frequency values indicates a change in the internal cell structure and/or the cell wall. Accordingly, we deduce that the antimicrobial agent has had a measurable effect on the bacteria, so the bacteria are susceptible to that particular antimicrobial agent. β-lactam antimicrobial agents inhibit cell wall synthesis and hence have an overall effect of increasing the volume (size, diameter) of the bacteria, as observed in  FIG.  10 ( b ) . 
       FIGS.  10 ( c ) and  10 ( d )  show two more scatter plots for samples of exposed and unexposed bacteria plus plastic beads, where the bacteria are a different strain from that of  FIGS.  10 ( a ) and  10 ( b ) .  FIG.  10 ( c )  shows data for a sample of the bacteria which has not been exposed to an antimicrobial agent. A contour line is drawn around the bacteria population as before.  FIG.  10 ( d )  shows data for a sample of the bacteria after exposure to the β-lactam antimicrobial agent. Very little difference from  FIG.  10 ( c )  can be observed; almost the whole bacteria population remains inside the contour line. Accordingly, we can deduce that the antimicrobial agent has had little, if any, measurable effect on the bacteria. The strain being tested are concluded to be resistant to the antimicrobial agent at this specific concentration. 
     As noted above, other classes of antimicrobial 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 the impedance measurement. A change in cell size is indicated by a change in the response at lower frequencies (the x-axis in  FIGS.  10 ( a )-( d ) ), and a change in cell wall/cell interior properties is indicated by a change in the response at higher frequencies (the y-axis in  FIGS.  10 ( a )-( d ) ). A reduction in the total particle population arising from compromised cell structure due to the antimicrobial agent to such an extent that it no longer registers as a particle is indicated by a reduced particle count in an accurately measured volume. Each of these changes produces a smaller number of data points inside a contour such as that shown in  FIGS.  10 ( a )-( d ) , either because the data points migrate outside the contour if the cell size or wall/interior structure changes, or because the data points are eliminated if the cell integrity is compromised. Accordingly, a comparison of the number of data points inside the same contour line for exposed and unexposed microorganism populations can be used to identify susceptibility. A metric representing susceptibility at a specific antimicrobial concentration can be defined as the number or proportion of microorganisms in an exposed sample that lie inside the contour drawn for the unexposed sample. For example, in  FIG.  10 ( b )  very few cells are left within the contour, and the metric is close to 0%; therefore the bacteria are susceptible to the antimicrobial agent at that concentration. In  FIG.  10 ( d )  most of the cells lie inside the contour, and the metric is close to 100%; therefore the bacteria are resistant to the antimicrobial. 
       FIGS.  11 ( a ) and ( b )  show some example scatter plots indicating susceptibility to an antimicrobial agent that reduces the total cell count by destroying the bacteria. For each plot, the electric radius for each cell at the low frequency, |Z 5 MHz | 1/3 , is plotted on the x-axis, and the normalised impedance value for each cell at the high frequency, |Z| 40 MHz /|Z| 5 MHz , is plotted on the y-axis, as with the  FIG.  10    graphs.  FIG.  11 ( a )  shows impedance measurements from an unexposed sample, including a population of bacteria, with a contour line or gate drawn to encompass the bulk of the population, and a population of reference beads at a larger high frequency response.  FIG.  11 ( b )  shows impedance measurements from an exposed population. The x-y position of the data has not moved significantly for the exposed bacteria, since there are few data points outside the contour, but the total cell count is substantially reduced, indicated by the smaller number of data points inside the contour compared with the unexposed sample. Therefore, the bacteria are classified as susceptible to the particular antimicrobial agent. 
     The example data described so far has been obtained using a high frequency and a low frequency for the signal applied to the signal electrodes in the apparatus. However, results may also be obtained by measuring at one frequency only. A scatter plot for a microorganism population may then be produced by plotting the impedance magnitude against the impedance phase. 
       FIG.  12    shows two further example scatter plots, of data obtained at a high frequency of 40 MHz only. 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 before, plastic microbeads were included in the samples; these appear at a phase value of about 1. Data points at lower phase values, around 0.7, indicate bacteria; hence phase measurements can readily distinguish between bacteria and beads.  FIG.  12 ( a )  shows a plot for a sample of bacteria that has not been treated with antimicrobial. The measured electric radii for the population range from about 1.5 to 2.1.  FIG.  12 ( b )  shows a plot for a sample of the same bacteria that have been exposed to an antimicrobial agent. The bacteria population has shifted to higher x-axis values, covering a range from about 1.8 to 2.7. Since it is known that exposure to an effective antimicrobial agent can alter bacterial cell size, we deduce that the bacterial strain is susceptible to the antimicrobial that has been applied. 
     Note that, in line with the ability to readily distinguish populations of bacteria from populations of beads by looking at the phase values, phase can also be used to distinguish between, or identify the presence of, populations or subpopulations (groups or sub-groups) of different microorganisms within one sample, if the different microorganisms have a different size and/or shape and/or morphology. The different microorganisms may by originally present in the sample, or may arise from an effect of the antimicrobial agent. For example, some agents change cell size with the effect of generating subpopulations of larger, smaller and intermediate persister cells. 
     As a further alternative, phase and magnitude values of the impedance at different frequencies may be combined.  FIG.  13    shows further example scatter plots for data obtained at 5 MHz and 40 MHz. As for the  FIG.  12    graphs, the  FIG.  13    graphs plot the phase at 40 MHz on the y-axis. The x-axis, however, shows the electric radius at the low frequency, 5 MHz.  FIG.  13 ( a )  shows measurements from a sample of bacteria untreated with an antimicrobial agent, and  FIG.  13 ( b )  shows measurements from a sample of the same bacteria that has been treated with an antimicrobial agent to which the bacteria are susceptible. The bacteria and the antimicrobial agent are the same as for the  FIG.  12    data. Both samples contained reference beads, having a phase value around 1. As with the  FIG.  12    data, the bacteria are easily distinguished from the beads, having a lower phase value around 0.7. Note that the phase values are the same as in  FIG.  12   , since the phase data is obtained for the same, high, frequency. Again as before, the treated bacteria show a shift to larger values of electric radius, arising from the susceptibility to the antimicrobial agent causing an increase in cell size. Note that in this example, the apparent increase in cell size is greater than in  FIG.  12   , to values in the range of about 2.1 to 3. This is owing to the greater sensitivity of cell size to low frequency measurements than high frequency measurements. 
     From these results, it may be appreciated that a method according to the present disclosure may be used to apply electric signals (voltages or currents) to the first and second signal electrodes at one frequency, or at more than one frequency. Accordingly, an apparatus used to carry out the method may comprise one or more electrical signal sources operable to generate one frequency, or two or more frequencies. The one frequency may a high frequency, or a low frequency. The two or more frequencies may comprise two frequencies, one high and one low. A high frequency may be in range of about 10 MHz or above, such as between 10 and 1000 MHz, for example 40 MHz. In some applications, even larger frequencies may be useful, such as frequencies up to about 10 GHz. The low frequency is smaller than the high frequency and may be in the range of 10 MHz or below, such as between 1 and 10 MHz, for example 5 MHz. Other and/or additional frequencies are not precluded, however, and can be chosen with reference to a particular application. Similarly, the ratio between the low frequency and the high frequency can vary greatly depending on the application. 
     As described above, for example with respect to  FIGS.  10 ,  11 ,  12  and  13   , a method in accordance with the present disclosure can comprise obtaining a measurement from a sample of microorganisms that have been exposed to a selected antimicrobial agent (where the microorganisms are particles suspended in an electrolyte to provide a fluid that is passed through an arrangement of electrodes 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 microorganism that have not been exposed to any antimicrobial agent, and comparing the two measurements. The unexposed microorganism population is used as a reference to which the exposed population is compared. Significant differences between the two measurements can indicate that the microorganisms are susceptible to the selected antimicrobial agent. The measurements can be arranged in scatter plots of data points corresponding to individual microorganisms, and the difference assessed by reference to a contour line around the population of unexposed microorganisms. A threshold value may be set, for example, so that if the antimicrobial exposure causes the number or the proportion of exposed microorganisms captured within the contour line to fall below the threshold, susceptibility is deduced. To obtain the two samples, a group of bacteria may be divided in half, before or after suspension in the electrolyte; one half is incubated with the antimicrobial agent and the other without antimicrobial agent, for a set period of time, such as 30 minutes. Then, the reference plastic beads can be added if desired, and both samples passed through an apparatus as described to obtain a differential signal from which impedance data can be derived. 
     However, it can be more useful to quantify antimicrobial susceptibility in more detail. In practice, susceptibility is more commonly defined as whether a microorganism strain is susceptible or resistant to a given concentration of antimicrobial agent. At very high concentrations, most antimicrobial agents will overcome microorganisms, but such high concentrations may not be safely or practically achievable in the human body. Under this approach, one can define a minimum inhibitory concentration, or MIC, which is the lowest concentration considered to have a noticeable inhibitory effect on the microorganism strain&#39;s population. Then, one can decide if the MIC is achievable in the human body, and hence if that particular antimicrobial agent can be used to combat infection caused by the particular microorganism. Therefore, it is useful to be able to measure the response of microorganisms to a range of different concentrations of an antimicrobial agent in order to determine the MIC. Methods according to the present disclosure are well-suited to enable this determination owing to their simplicity. 
     A method in line with the description thus far can be extended by dividing a sample of microorganisms into more than two groups, and exposing each group to a different concentration of antimicrobial agent, including an unexposed group to act as a reference sample, as before. In this way a MIC can be determined, or a previously-established value for the MIC can be verified or re-tested. To assess a MIC, groups or populations of microorganisms at similar concentrations are incubated with a range of antimicrobial concentrations, which are usually a control or reference concentration of 0, a concentration considered to be a clinically relevant MIC, and two or more concentrations (or dilutions) on either side of the MIC. Hence, the sample of microorganisms is divided into six groups, each of which undergoes an impedance measurement. 
     As an example, the microorganism sample for performing MIC assessment may comprise picking a colony of microorganisms from a plate and incubating the colony overnight in suitable media, such as trypticase soy broth (TSB) to produce a culture. An aliquot of the culture is diluted into Mueller Hinton broth (MHB) to a concentration of 5×10 5  cells/mL and incubated at 37° C. for 30 minutes to obtain an actively dividing culture. Aliquots (950 μL) of the actively dividing culture are added to each of seven prewarmed test tubes each containing 50 μL of MHB and a dose of antimicrobial, such as the antibiotic meropenem, to give a set of final antimicrobial 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 Hanks balanced salt solution (HBSS) and subsequently diluted 1:10 in HBSS. 1.5 μm diameter reference beads are added to each sample (10 4 /mL) Impedance flow cytometry measurements can then be carried out as described above, for example by using a syringe to introduce the sample into the cytometer apparatus at a rate of 30 μL/min for 3 minutes. 
       FIG.  14    shows six scatter plots of impedance measurements from six groups of bacteria exposed to a series of six antimicrobial concentrations. In this example, the concentrations were 0 μg/mL (control), and 0.5, 1, 2, 4 and 8 μg/mL as indicated on the graphs, where 2 μg/mL is the known, pre-defined MIC of the antimicrobial agent for the bacteria being tested.  FIG.  14 ( a )  shows the control or reference population not exposed to the antimicrobial agent, with the gating contour drawn around the bacteria population to encompass the majority of the data points. For the lower antimicrobial concentrations ( FIGS.  14 ( b )-( d ) ), the bacteria can be seen to be resistant, since the data points are not moved out of the contour. Only at concentrations of 4 and 8 μg/mL is a significant shift out of the contour observed ( FIGS.  10 ( e ) and ( f ) ). For these measurements, the data was obtained at two frequencies, a low frequency of 5 MHz and a high frequency of 40 MHz. The impedance value for each cell at the low frequency, |Z| 5 MHz , is plotted on the x-axis, and the normalised impedance value for each cell at the high frequency, |Z| 40 MHz /|Z| 5 MHz , is plotted on the y-axis. 
     As discussed, the measured “shift” in biophysical properties arising from exposure to an antimicrobial agent to which a microorganism strain lacks resistance, and discernible as a change in the cell count inside a contour marking a distribution of impedance measurements from an unexposed population, may be quantified in a number of different ways, including a change in cell size, a change in cell wall/membrane properties, and/or a decrease in cell count, or a combination of these. 
       FIG.  15    shows graphs which summarise measurements of these properties for ten different strains of bacteria after exposure to different antimicrobial concentrations, where the values of the various properties are determined from impedance measurements obtained by methods according to the present disclosure.  FIG.  15 ( a )  shows the total cell count normalised to a reference cell count (y-axis) against antimicrobial concentration (x-axis).  FIG.  15 ( b )  shows the number of cells inside a contour gate normalised to a reference number (y-axis) against antimicrobial concentrations (x-axis) (and is hence similar to the total cell count in  FIG.  15 ( a ) ).  FIG.  15 ( c )  shows the cell size normalised to a reference cell size (y-axis) against antimicrobial concentration (x-axis).  FIG.  15 ( d )  shows the opacity normalised to a reference opacity (y-axis) against antimicrobial concentration (x-axis). The group of lines A correspond to bacteria that are known to be highly resistant to the antimicrobial agent, so the properties are not affected much even at higher concentrations; the lines remain largely horizontal. The group of lines B show strains which are moderately resistant, so the properties are altered only at higher concentrations; the lines deviate from the horizontal at higher concentrations. The group of lines C shows strains which are known to be highly susceptible to the antimicrobial agent, so the properties are altered even at very low concentrations; the line deviate from the horizontal immediately the concentration exceeds zero. These four different graphs could be used separately or together to make a quantitative decision of the susceptibility of the bacteria. As an example, the total bacteria count in  FIG.  15 ( a )  for the C group is lower at 0.25 μg/mL (so the bacteria are susceptible at this concentration), but the lines of the B group only show a decrease in cell count at 4 μg/ml. A similar trend can be identified in the cell size shown in  FIG.  15 ( c ) . A threshold could be defined to determine an appropriate MIC. For example, one could require that the cell size has to increase to 110% or above for the antimicrobial agent to be considered effective; the concentration that produces this change is taken as the MIC. Different antimicrobial agents and different microorganisms will have different profiles, resulting in different thresholds for the various properties to quantify the susceptibility and make a determination of susceptible or resistant for each isolate/antimicrobial agent concentration. The data could be analysed/correlated and/or calibrated against standard techniques for the measurement of susceptibility. 
     A drawback with the technique of optical cytometry is that the antimicrobial agent often has to be removed from a sample by a washing step before the necessary dye is added. This is because the dye can interfere with the growth of microorganisms. Hence the sample only captures the antimicrobial agent effect at the time of washing, and the optical measurement provides a “snapshot” only. This would prevent the study of the evolving effect of the antimicrobial agent over time without preparing a multiplicity of samples each washed after a different incubation time, which is both inconvenient, and expensive owing to the costly nature of the dyes. This latter point would make it expensive to assess MIC via optical cytometry owing to the need for a plurality of samples at different antimicrobial concentrations. 
     The methods of impedance flow cytometry described herein address this issue by enabling a continuous impedance measurement from a single microorganism sample, so that the evolution of the antimicrobial effect of an agent can be assessed. To achieve this, a single microorganism population is prepared in an electrolyte solution such as a growth medium as a fluid to be passed through an impedance measurement apparatus as described above, and an antimicrobial agent is applied to the microorganisms, and remains in the sample. The fluid, including the microorganisms and the antimicrobial agent, is passed into the apparatus flow channel promptly so that a first impedance measurement can be recorded soon after addition of the antimicrobial agent, for example within the first minute. On this time scale, the antimicrobial agent may not have a measurable effect on the microorganisms, so the microorganisms could be considered to be unexposed to the antimicrobial agent and this first measurement can be taken as a reference measurement corresponding to a measurement from an unexposed microorganism sample. The passage of the fluid through the flow channel is maintained at a constant rate, either by continuous extraction from a large sample, or by recirculation of fluid from a smaller sample, and multiple measurements are obtained, each at a specified time, for example, at intervals of one minute after the first, reference, measurement. Alternatively, measurements may be obtained on a continuous basis, and the results divided into data collected within successive time periods or bins, such as one minute intervals. Over the total measurement time, the antimicrobial agent continues to act on the microorganisms, and its effect over time can be determined by comparing the different measurements. The portions of the sample corresponding to each time interval can be considered as sub-samples, for each of which impedance measurements are gathered. In some cases, it may be desirable to add the antimicrobial agent to the sample after measurement on the sample has begun, if for example the antimicrobial agent acts quickly on the microorganism. This allows the first measurement to be a reference measurement from unexposed microorganisms. To achieve this, a single microorganism population can be prepared in an electrolyte solution such as a growth medium to obtain a fluid to be passed through an impedance measurement apparatus as described above. A measurement or multiple measurements are taken, and then the antimicrobial agent is added to the fluid. Measurements then continue on the exposed sample as described above. 
       FIG.  16    shows a sequence of scatterplots of data obtained in this way, using a high frequency of 40 MHz and a low frequency of 5 MHz to obtain impedance measurements. A population of bacteria was exposed to antimicrobial agents and measured continuously over 26 minutes, and the resulting impedance data separated into bins corresponding to one minute intervals, and plotted on a graph. The sample fluid included plastic microbeads which appear as a population group in the upper left of each graph, as in previous examples. The upper left plot shows the data collected in the first minute (time of 0 to 1 minutes) which is designated as the reference or control data for unexposed bacteria. A contour line or gate is drawn around the unexposed bacteria population in this graph, and then replicated in each later graph so that alteration of the bacteria over time can be identified. A study of the sequence of graphs reveals that after about 15 minutes, the bacteria population starts to shift noticeably out of the contour line. Hence, we can deduce that the bacteria is susceptible to the particular antimicrobial agent. After 26 minutes, almost the whole population has moved out of the contour. Movement is to higher low frequency values, indicating an increase in cell size, and to a lesser extent to lower high frequency values, indicating that the antimicrobial agent also changes properties of the bacterial cell wall or its internal structure. 
       FIG.  17    shows a further example apparatus, with an alternative arrangement of electrodes. Eight electrodes are provided to define four current paths, in two groups each comprising a first current path and a second current path, as in some preceding examples. However, while preceding examples have comprised only one current path orientation within a single system, the  FIG.  17    example includes two orientations of current path, which enables additional information to be determined about particles in a sample. 
     In particular, the apparatus is configured so that in each of the first electrode group  50  and the second electrode group  52 , there is a current path which is substantially transverse to the fluid flow direction and a current path which is substantially parallel to the fluid flow direction. In the first electrode group  50 , a first signal electrode  60   a  supplied with +V from a voltage source  70  is arranged above the channel, opposite to a first measurement electrode  62   a  below the channel, to define a first current path transverse to the flow direction, from which a current I 4  is measured. A second signal electrode  64   a  supplied with −V from a voltage source  72  is arranged below the channel adjacent to a second measurement electrode  66   a  also below the channel, to define a second current path which is parallel to the flow direction, from which a current I 3  is measured. As before, I 3  and I 4  are combined to produce a first summed signal I 5 , from the first electrode group  50 . Similarly, in the second electrode group  52 , a further first signal electrode  60   b  is opposite to a further first measurement electrode  62   b  to define a transverse first current path I 6 , and a further second signal electrode  64   b  is adjacent to a further second measurement electrode  66   b  to define a parallel second current path I 7 . I 6  and I 7  are combined to generate the second summed signal I 8 , and as in previous examples, the summed signals are handled by current to voltage converters  34   a ,  34   b  and a differential amplifier  36  to determine a differential signal. 
     The provision of differently oriented current paths along the same flow path can reveal information about particle shape. In the absence of any particle, the magnitudes of the various current paths are approximately equal, summing to approximately zero, as before. In the presence of a spherical or near-spherical particle, as described with respect to  FIGS.  1  to  9   , the impedance signals measured for transverse current paths have approximately the same magnitude as the impedance signals measured for parallel current paths. However, if a particle  42   a  is non-spherical, such as an elongate rod-shaped bacteria (for example a  bacillus ), it will interact by different amounts with the two current path directions, giving differently-sized signals. If the elongate particle has its longest axis arranged along the channel flow direction, it will produce a larger change in the transverse current path than in the parallel current path. Accordingly, the summed signal derived from the two current paths within an electrode group will be different for an elongate particle compared to a spherical particle, the difference being related to the degree by which the particle shape differs from a sphere (in other words, its degree of eccentricity or elongation). Therefore, obtaining the summed signals from current paths of two different orientations (such as a transverse path and a parallel path) provides a differential signal that can indicate information about particle eccentricity or shape. This is useful for distinguishing between different types of bacteria, such as bacilli (rods) and cocci (spheres), or identifying chains of bacteria. Additionally it can be used to enhance the measurement of AST by identifying particles that have been arrested during the division cycle, as is the case for treatment with β-lactam antimicrobial agent. It is known for example that treatment of cells with different concentrations of β-lactam antimicrobial agents leads to different and distinct morphological forms. Antimicrobial agents acting at an early block point give dumbbell shapes whereas those affecting at a later time give lemon-shaped cells M J Pucci et al, Bacteriology 165 682-688, 1986. 
     The external shape of a particle can reveal other properties. For example, if the flow of the sample fluid through the cytometer channel creates sufficient shear stress, a cell can be deformed or squashed as it travels along the channel. Softer cells will be deformed more than stiffer cells, acquiring a greater degree of eccentricity. Accordingly, an arrangement as in the  FIG.  17    example that uses current paths of different orientations to detect cell eccentricity, can additionally be used to distinguish or determine mechanical properties of particles. A softer particle will produce different summed signals and differential signal than a stiffer particle, owing to the different shape induced by the flow. The action of an antimicrobial agent on a microorganism species may also produce changes in mechanical properties. 
     Note that the electrodes might be positioned to provide the two orientations of current path in a different order along the flow direction than that shown in  FIG.  17   .  FIG.  18    shows a scatterplot of impedance data obtained from two different cell types. As before, each data point represents a single particle in a sample. The vertical axis shows a “deformability” measure, obtained by dividing the impedance measurement from one or more parallel current paths by the impedance measurement from one or more transverse current paths. The horizontal axis indicates the electrical diameter of the particles, obtained by averaging the impedance signals from the two measurement directions, which approximates cell size. Alternatively, the diameter might be obtained in line with the measurement of electrical radius discussed with regard to  FIG.  12   . Measurements were obtained for two groups of B3Z cells, which have a spherical shape. One group was modified by a fixing treatment with glutaraldehyde to increase the membrane stiffness. Note that the measurement could be made on a single sample containing both groups of cells, or on two samples, each containing one group. The cells in the two groups therefore have different mechanical properties, and appear on the scatterplot as two well-separated populations. Measurements of a reference population of 7 μm beads is also indicated. The stiffer, fixed cells remain substantially spherical in the fluid flow along the channel, so the impedance signals measured for the two orthogonal current paths are similar. Hence the deformability for these cells is measured as near to 1 arbitrary unit. In contrast, the unfixed cells are deformed by the flow and stretch out along the channel direction. Accordingly, the impedance signals measured along the channel direction are reduced compared to the measurements across the channel, and the deformability measure is reduced below 1 AU. In this example, it is measured at about 0.5 AU. Thus, mechanical properties of individual cells and populations of cells can be identified, and different cell populations can be distinguished one from another. 
     The technique of assessing antimicrobial susceptibility by determining the minimum inhibitory concentration (MIC) has been described above, together with an indication of how to carry this out using the described impedance flow cytometry methods. An alternative technique is that of breakpoint analysis, in which bacteria samples are exposed to one or two concentrations of antimicrobial (antibiotic) and classified as susceptible/not susceptible (S/NS), resistant/not resistant (R/NR), or of intermediate resistance, depending on the response of the samples to the antimicrobial. The response can be measured using the described impedance flow cytometry. 
     In breakpoint analysis, bacteria are assessed at one or two pre-defined concentrations of antibiotic that are tabulated by standards institutes such as the Clinical &amp; Laboratory Standards Institute (CLSI) in the USA and the European Committee on Antimicrobial Susceptibility Testing (EUCAST). To perform the analysis, bacteria growth is assessed at a first concentration X, which sets a boundary for S/NS. If the bacteria do not grow (i.e. the number of bacteria in the tested sample does not increase) they are classified as susceptible to the antibiotic. If the bacteria grow, they are classified as not susceptible to the antibiotic. Additionally, growth of the bacteria can be assessed at a second concentration Y, which is higher than concentration X and sets a boundary of R/NR. If the bacteria grow, they are classified as resistant to the antibiotic; if they do not grow, they are classified as not resistant. The values of concentration X and concentration Y depend on the strain of bacteria 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 also not susceptible, a characteristic commonly termed as intermediate resistance. For some antibiotics and some bacteria species, there is no intermediate region, in other words, concentration X and concentration Y are equal, and testing at only one concentration is required. In either case, a sample of bacteria that has not been exposed to the antibiotic is also tested using the impedance flow cytometry in order to obtain the reference population gate or contour described above. 
     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. This sample is vortexed to resuspend the bacteria in the broth, and then diluted to a concentration of 5×10 5  cells/mL in MHB. The sample is then incubated for thirty minutes to obtain an actively dividing culture. Aliquots of 500 μL are added to test tubes containing 500 μL of pre-warmed MHB each with a final antibiotic concentration at the clinical breakpoint (S/NS and/or R/NR), for example according to current EUCAST guidelines. These might be 2 mg/L (S/NS) and 16 mg/L (R/NR) for the antibiotic meropenem, or 1 mg/L for ciprofloxacin, or 8 mg/L for gentamicin, or 4 mg/L for colistin, or 8 mg/L for ceftazidime, amoxicillin/clavulanic acid and cefoxitin, along with a control sample at 0 mg/L. Each tube is incubated for thirty minutes (antibiotic exposure) before the sample are diluted at a level of 1:10 in HBSS, and 1.5 μm reference beads are added. The samples can then be passed through an impedance flow cytometry apparatus at a rate of 30 μL/min for a measurement period of 2 minutes. 
       FIG.  19    shows bar charts of example data measured using impedance flow cytometry to perform breakpoint analysis. Eleven different strains of bacteria were exposed to the antibiotic meropenem. The charts show, for each strain, the percentage of the bacterial population remaining in the reference gate or contour (measured for an unexposed sample of the bacteria) after exposure to the antibiotic.  FIG.  19 ( a )  shows data for the susceptible/not susceptible (S/NS) breakpoint, for which the antibiotic concentration is 2 mg/L and  FIG.  19 ( b )  shows data for the resistant/not resistant (R/NR) breakpoint, for which the antibiotic concentration is 16 mg/L. The bacteria are labelled as KP ( Klebsiella pneumonia ), EC ( Escherichia coli ), ACB ( Acinetobacter baumannii ) and PAE ( Pseudomonas aeruginosa ). The bars show a mean value ±the standard deviation (N=3; *p&lt;0.05; **p&lt;0.01; ***p&lt;0.001 with p-values obtained using the Student&#39;s t-test for independent samples (one tailed)). The shading of the bars represents susceptibility and resistance determined by the conventional technique of broth microdilution, where darker bars are resistant strains and paler bars are susceptible strains. There is good correspondence between these designations and the measured percentage of cells in the control gate, indicating impedance flow cytometry is an accurate technique for performing breakpoint analysis. The intermediately shaded bar in each chart is for KP (CNCR) which is a carbapenemase negative strain of KP that is resistant to carbapenems. 
       FIG.  20    shows a set of scatter plots of data obtained using impedance flow cytometry for resistant and susceptible strains of three bacteria,  Klebsiella pneumonia  (KP),  Escherichia coli  (EC), and  Staphylococcus aureus  (SA) exposed to different antibiotics, indicated in the heading of each scatter plot. The various antibiotics have different mechanisms of action to alter the cell size, shape, structure and/or count, leading to different impedance responses which can be detected by the impedance flow cytometry. This can be appreciated from the various different movements of the data points indicating the cell populations relative to the gate contours. The resistant bacteria are unaffected by the antibiotics, so the populations remain approximately within the gate contours. The susceptible bacteria are affected by the antibiotics, so the populations are altered with respect to the size, shape and position of the gate contours. The antibiotic concentrations were at the R/NR breakpoint concentrations for the various bacteria strain/antibiotic combination. 
     The scatter plots for the antibiotics Colistin, Gentamicin, Ciprofloxacin, Ceftazidime and Co-amoxiclav are shown as electric cell size or radius (being the cube root of the measured low frequency (5 MHz) impedance as explained above) against electrical opacity (being the measured high frequency impedance (40 MHz) normalised to the low frequency impedance as explained above). The scatter plot for Cefoxitin is shown as electric cell size against the measured high frequency (40 MHz) phase impedance because this measure gives a clearer difference between resistant and susceptible for the particular antibiotic mechanism of Cefoxitin. 
     Also included in  FIG.  20    is a bar chart similar to those of  FIG.  19   , showing the percentage of cells remaining in the gate contour for each bacteria/antibiotic combination. Again, the darker shading and the paler shading correspond respectively to resistance and susceptibility determined by conventional broth microdilution, to show that comparable results are obtainable using impedance flow cytometry. 
     Considering phage susceptibility specifically, there are a number of molecular events that occur during phage infection which are evident from the impedance cytometry data and would be important considerations in deciding whether a bacterial isolate was susceptible to any given phage. The molecular events include, but are not limited to, initial binding of the phage to the cell (e.g. change in opacity), loosening of the bacterial outer membrane and peptidoglycan layer due to effects of phage depolymerases either alone or in combination with phage lysins (e.g. change in opacity; change in electrical radius), replication and generation of progeny phage within the bacterial cell (e.g. increase in electrical radius as the bacteria swells), effects of phage holins resulting in selective permeabilization of the cytoplasmic membrane and disruption of the proton motif force (e.g. change in opacity), cell lysis and rupture mediated by phage lysins (e.g. change in opacity; reduction in total number of impedance signals), inhibition of growth (e.g. reduction in cell impedance signals relative to uninfected control sample or reference). One or more of these events can be interrogated using the methods of the invention. Each molecular event can lead to a change in one or more characteristics including opacity; electrical volume; electrical radius; total number of impedance signals. Importantly, many of these events are not evident from other optical/fluorescent flow cytometry methods, which are not able to assess the direct impact of the phage, or other antimicrobial agent, on the bacterial membrane. These important events are not part of the output of prior art methods that a clinician or other practitioner could use to make decisions about suitability of a particular phage or phage cocktail for treatment, but which the methods of the invention can provide evidence for. As the bacterial impedance flow cytometry method looks at physical events in single bacteria, it also provides information that is not evident when other electrical impedance techniques, which measure changes in the media due to bacterial metabolism. This enables both more rapid assessment of susceptibility to phage and more detailed analysis on which to base selection of particular phage for treatment. Importantly, this includes the presence of a low frequency of phage-resistant bacterial cells in a population, which is either present intrinsically in a population (often termed heteroresistance) or which may emerge over time due to selective pressure. Being able to observe changes at the level of individual bacteria is highly preferable compared to measuring metabolic changes that are representative of the population as a whole and which may be relatively insensitive to low frequency changes. 
     Similarly, with respect to antimicrobial peptides, a number of events can be observed using the impedance flow cytometry method. These include, but are not limited to, binding to the cell (e.g. change in opacity), disruption of the LPS layer, outer membrane or peptidoglycan (e.g. change in opacity), permeabilization of the inner membrane resulting in either leakage or dissipation of the proton motive force (e.g. change in opacity; loss of impedance signals relative to controls) and cell lysis (e.g. reduction in number of cell impedance signals in total or relative to control), inhibition of growth (e.g. reduction in number of impedance signals relative to untreated control or reference). One or more of these events can be interrogated using the methods of the invention. Each molecular event can lead to a change in one or more characteristics including opacity; electrical volume; electrical radius; total number of impedance signals. Similar considerations relate to monitoring antimicrobial peptide activity using bacterial impedance flow cytometry compared to other methods, as described above. Importantly, many of these events are not evident from other optical/fluorescent flow cytometry methods, which are not able to assess the direct impact of the antimicrobial peptide on the bacterial membrane. This enables both more rapid assessment of susceptibility to antimicrobial peptides and more detailed analysis on which to base selection of particular antimicrobial peptide for treatment. Importantly, this includes being able to identify the presence of a low frequency of resistant bacterial cells in a population. 
     Impedance flow cytometry methods according to the examples and embodiments herein offer a number of benefits. Testing and measurements can be carried out quickly and with an improved sensitivity, particularly for smaller particles such as bacteria so the methods are valuable for AST and other microorganism assays. Apparatus suitable for performing the methods can be compact, potentially portable, and inexpensive, such as a chip-based format which lends itself to mass production, and scalability for multiple simultaneous tests. In the context of testing microorganism susceptibility to antimicrobial agents, tests can be prompt and simple, and inexpensive since no dye or other labelling medium is required. This also enables continuous monitoring of the response of any given sample to antimicrobial agents over an extended time period, which is not typically possible in dye-based testing procedures such as optical cytometry. 
     As an example of the improved speed of testing offered by impedance flow cytometry, consider the case of a patient on an intensive care ward who presents with a urinary tract infection and is immediately prescribed the antibiotic co-amoxiclav as the conventional standard to care for this condition. The patient sample is sent for testing within the hospital microbiology unit and after an overnight culture of the bacteria taking approximately 16 hours from collection of the sample, the isolate is identified as  E. coli  using, for example, a Biotyper system manufactured by Bruker, which takes another 2 hours or so. This identification can lead to a change in antibiotic to a type considered more suitable, followed a further period of a day or so in which observation of the patient indicates whether the bacteria is resistant to the antibiotic, in which a further change of antibiotic may be required. In contrast, rapid AST using an impedance flow cytometer performed at the 16 hour mark with one or more antibiotic types can identify an antibiotic to which the bacteria is susceptible in a period of just 30 minutes, so that the prescription can be optimised. For example, it may be found that the  E. coli  strain is resistant to co-amoxiclav, but susceptible to meropenem. 
     Methods described herein may be used to measure and analyse particles of non-biological origin, so examples may be considered more generally as particle impedance measurement methods, which may be performed using apparatus configured (for example as regards its dimensions) for use with biological particles (in particular cells which may or may not be bacteria) or non-biological particles, or any particle type. The terms “impedance flow cytometry”, “impedance flow cytometry method”, “impedance flow cytometer” and “impedance flow cytometry apparatus” are intended to cover any method and apparatus as described herein regardless of the nature of the particles, although in some examples the particle type is relevant, such as impedance flow cytometry for AST and MIC determination. The disclosure is not limited in this regard. 
     The impedance flow cytometry can be used to measure the electrical (impedance) properties of bacteria without any dyes. The technique can directly measure the phenotypic response of an organism and does not require incubation with a dye. Furthermore, the technology can be carried out on compact and scalable apparatus, so that several measurements can be made in parallel using a custom design of chip with multiple channels. The electrical properties can be measured continuously as a function of time to determine the evolution of the response to antimicrobials. This is not usually done using dyes as they are washed away prior to measurements. 
     Prophylactic Phage Therapy for Improved Prevention or Control of Bacteria Causing Chronic Diseases 
     Phage therapy can be used to prevent or control microorganisms causing chronic diseases. Phage therapy has the advantage that phage target specific species so specific organisms can be targeted with reduced interference with the microbiome. Bacterial impedance flow cytometry can be used to identify phage to which the microorganism contributing to a particular chronic condition are susceptible. The following microorganisms associated with acute and chronic conditions are possible targets for which suitable phage therapy can be identified using the methods described herein:  B. fragilis  strains carry a genetic element that encodes a metalloprotease enterotoxin named  Bacteroides fragilis  toxin, or BFT. Toxin-bearing strains, or Enterotoxigenic  B. fragilis  (ETBF) cause acute and chronic intestinal disease in children and adults. 5,6    
     The exotoxin-secreting gut bacterium  Enterococcus faecalis  is a critical contributor to alcoholic hepatitis 7    
     Studies by various authors have linked the presence of colibactin producing Enterobacteriaceae with colorectal cancer. 8-10 . Phage have been proposed to play a role in prevention and/or treatment of colorectal cancers 16-18    
       Fusobacterium nucleatum  is linked to ulcerative colitis in the gut 11 , development of colorectal cancer 12  and to treatment failure in different forms of cancer therapy 13 . Phage have been isolated for  F. nucleatum   14  and shown to disrupt biofilms 15    
       K. oxytoca  is a resident of the human gut, yet in some patients taking penicillin, expansion of this pathobiont results in antibiotic associated hemorrhagic colitis (AAHC); the causative agent is a PBD derivative termed tilivaline 1    
     Individual strains in various species of gamma Proteobacteria (e.g.  Acinetobacter baumannii, Klebsiella pneumoniae, Proteus mirabilis, Providencia  spp,  Citrobacter  spp) with genes associated with choline and carnitine metabolism, and/or which generate trimethylamine which is linked to cardiovascular disease in humans 2-4 . 
       Pseudomonas aeruginosa, Stenotrophomonas maltophilia, Burkholderia cepacia, Burkholderia cenocepacia, Burkholderia multivorans, Achromobacter  spp.  Pandoraea  spp and  Ralstonia  spp. Species are all associated with chronic infection/long term colonisation of patients with cystic fibrosis. 
     Example 1: Assessment of Phage Susceptibility Using Bacterial Impedance Flow Cytometry (BIC); Single Phage Preparations 
     1.1 Method for Determining Bacterial Impedance how Cytometry Profile 
     The protocol uses bacteria, e.g. from a clinical sample plated onto TSA or selective plates and grown overnight at 37° C. Preferably, the plates are freshly cultured prior to use. Three colonies are picked from the plates, inoculated into 3 mL of broth and incubated at 37° C. for 30 minutes with shaking. To standardise the number of bacteria used for the experiment, the growing culture can be compared with McFarland Standards. Preferably, cell counts are performed on the bacterial impedance flow cytometry platform by diluting 200 μL of culture into 790 μL PBS+10 μL of a stock of size standard beads (1 μL of bead stock diluted into 1 mL PBS). The number of cells in 15 μL of sample were calculated using the bacterial impedance flow cytometry ‘cell count’ function of the script ‘ImpedanceGUI_V1’. This allows the number of colony forming units (CFU) per ml to be calculated. Bacteria are diluted to a starting concentration of 5.5×10 5  CFU/mL. Bacteria were diluted into an aliquot of 12 mL which was then separated into 4×3 mL aliquots for assessment of phage susceptibility. 
     Phage preparations were prepared using standard methods and the stocks either filtered through 0.2 μm filters and/or partially purified using PEG precipitation from bacterial culture supernatants. Phage were titred, using the standard microbiology methods described in Example 2 and maintained as working stocks at 4° C. Phage at an appropriate concentration are added to the bacterial suspension such that there is an excess of phage to bacteria. Typically, phage are added at a multiplicity of infection of 10 to 100 fold (phage to bacteria). The cultures containing phage and bacteria were incubated for up to 90 minutes at 37° C. in a static incubator, prior to analysis. 
     At the end of the incubation, the samples are analysed by bacterial impedance flow cytometry. 
     
       
         
           
               
             
               
                 TABLE 1 
               
             
            
               
                   
               
               
                 Phage used in the experiments 
               
            
           
           
               
               
               
               
               
            
               
                   
                 Propagating/ 
                 Stock Conc. 
                 Phage 
                 Phage 
               
               
                 Phage 
                 Susceptible host 
                 (pfu a /ml) 
                 family 
                 properties 
               
               
                   
               
               
                 Phage Ab_1 
                 
                   A. baumannii 
                 
                 5 × 10 9   
                 Myoviridae 
                 Lytic 
               
               
                   
                 NCTC 13302 
               
               
                 Phage Ab_2 
                 
                   A. baumannii 
                 
                 8 × 10 9   
                 Siphoviridae 
                 Lytic 
               
               
                   
                 ATCC 17978 
               
               
                 Phage Pa_1 
                 
                   P. aeruginosa 
                 
                     6 × 10 10   
                 Siphoviridae 
                 Lytic 
               
               
                   
                 PAO1 
               
               
                   
               
               
                   a Plaque forming units 
               
            
           
         
       
     
     
       
         
           
               
             
               
                 TABLE 2 
               
             
            
               
                   
               
               
                 Bacterial strains used in the study. 
               
            
           
           
               
               
               
            
               
                 Species 
                 Strain 
                 Resistance profile 
               
               
                   
               
               
                 
                   A. baumannii 
                 
                 NCTC 
                 Gentamicin-resistant; Imipenem-sensitive; 
               
               
                   
                 10303 
                 Colistin-Sensitive; Ciprofloxacin-Resistant; 
               
               
                   
                   
                 Piperacillin/tazobactam -sensitive 
               
               
                 
                   A. baumannii 
                 
                 NCTC 
                 Gentamicin- Resistant; Imipenem -Resistant; 
               
               
                   
                 13302 
                 Colistin-Sensitive; Ciprofloxacin-Resistant; 
               
               
                   
                   
                 Piperacillin/tazobactam -Resistant 
               
               
                 
                   A. baumannii 
                 
                 ATCC 
                 Gentamicin- Resistant; Imipenem -Sensitive; 
               
               
                   
                 17978 
                 Colistin-Sensitive Ciprofloxacin-Resistant; 
               
               
                   
                   
                 Piperacillin/tazobactam -Sensitive 
               
               
                 
                   A. baumannii 
                 
                 ATCC 
                 Gentamicin- Resistant; Imipenem -Sensitive; 
               
               
                   
                 17978 
                 Colistin-Resistant Ciprofloxacin-Resistant; 
               
               
                   
                 ColR 
                 Piperacillin/tazobactam -Sensitive 
               
               
                 
                   P. aeruginosa 
                 
                 PAO1 
                 Gentamicin- Resistant; Imipenem -Sensitive; 
               
               
                   
                   
                 Colistin-Sensitive Ciprofloxacin-Resistant 
               
               
                   
                   
                 Piperacillin/tazobactam -Sensitive 
               
               
                   
               
            
           
         
       
     
     1.2 Analysis and Interpretation of Data. 
     Data generated by the method shows clear differences in the susceptibility profile of individual phage/bacteria combinations as shown in  FIGS.  21  to  24   : 
       FIG.  21    shows a time course of bacterial impedance flow cytometry profiles for, A. susceptible (NCTC 13302) and, B. non-susceptible (NCTC 10303) strains of  A. baumannii  treated with Phage Ab_2. Scatterplots show the distribution of the impedance measured for individual bacteria at 15 minutes (T15) through to 90 minutes (T90). The standard method was followed with the exception that a low multiplicity of infection (Mol 0.1; 1 phage to 10 bacteria), was used. The spread in electrical radius measurements is increased in the susceptible sample. The mean and the modal electrical radius in the susceptible sample has also increased. A threshold test involving the spread of the Electrical radius results or the average value of the radius for the cohort of measurements centred around a particular phase, e.g. 0.5, or at a particular phase, could discriminate between a susceptible strain, e.g.  A. baumannii  (NCTC 13302) and a non-susceptible strain e.g.  A. baumannii  (NCTC 10303). The bacterial impedance cytometry profile has a different phase and opacity from e.g. microbeads. This can be used to distinguish other components for example microbeads from the bacterial profile which has a known phase.  FIG.  22    presents analysis of the data shown in  FIG.  21    as a bar chart. Analysis of the data shown in  FIG.  21    demonstrates a significant reduction in the total cell count (A), expressed as a percentage increase over the number of cells at 15 minutes, in the susceptible strain (shown on right hand side at each time point with hatching) compared to the resistant strain (shown on left hand side at each time point without hatching). A small residual increase in the susceptible population is observed over the 90 minute incubation, reflecting the scenario where not all bacteria in the population are infected with phage, consistent with the low Mol (0.1) used in this experiment. The data was further analysed to show the proportion of cells that sit within a contour that encloses 95% of a normal untreated bacterial population (B). This further shows the migration of viable bacteria out of 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 for the resistant strain of  A. baumannii , where the numbers of cells gated within the contour continued to increase rapidly during the time-course and no significant number of cells with increased volume were observed. 
       FIG.  23    presents bacterial impedance flow cytometry profiles obtained in an experiment carried out to assess the effect of treatment of a population of susceptible strain of  A. baumannii  NCTC 13302 with a high phage concentration (Mol=10 across a time course from 0 (TO) to 60 minutes (T60).  FIG.  23 A  presents bacterial impedance flow cytometry profiles obtained from a sample of the susceptible strain after treatment with a high phage concentration.  FIG.  23 B  presents bacterial impedance flow cytometry profiles obtained from a sample of the same susceptible strain which was not treated with phage. 
       FIG.  24    presents analysis of data shown in  FIG.  23 A  from an infection of NCTC 13302 with Phage Ab_2 at an Mol of 10. The data show a reduction in the total viable count (A) and a rapid migration of phage-treated bacteria (shown on LHS at each time point with hatching) out of the contour region, within 30 minutes, indicative of increased cell size (B) both compared to an untreated control culture (shown on RHS at each time point without hatching), incubated for the same time. 
     The data shows that phage infection of susceptible strains is linked to a decrease in the viable count either alone or in combination with a reduction in cell numbers within a contour defined by the 95th percentile of a control population. This control population can be defined either on the basis of a control culture incubated in parallel to the phage-treated population or by using the TO sample of the phage-treated sample as a control. The migration out of the contoured region, demonstrates a shift on the X-axis indicating an increase in the electrical radius of the cell; this is an indirect measure of the cell volume. This migration pattern, seen only in susceptible bacteria, is due to the propagation of phage within the cell, leading eventually to its rupture and release of phage progeny. This phenotype is observed within 15 minutes of phage addition at high Mol, in susceptible cells, and could mean that this is sufficient to identify susceptibility of clinical isolates. This gives a time to result of between 15 and 120 minutes for a bacterial impedance flow cytometry-based phage susceptibility test, e.g. for a rapidly growing bacterial species. For slow or very slow growing bacteria, such as  Mycobacterium , the times taken for a susceptibility measurement may need to be extended to 4 hours or 8 hours. 
     1.3 Generation of Bacterial Strain Susceptibility Matrix Using Individual Phage Stocks. 
     To validate the utility of the bacterial impedance flow cytometry test for rapid evaluation of the susceptibility of a bacterial isolate to phage, a study was carried out to validate a matrix approach to informing possible phage treatment. Four drug-resistant and in some cases multidrug-resistant isolates of  Acinetobacter baumannii  and  Pseudomonas aeruginosa , were incubated with each of three phage preparations according to the standard protocol described above and susceptibility measured by bacterial impedance flow cytometry. The matrix below demonstrates the susceptibility of the different isolates to each of the phage. The data can be used to identify a combination of phage which could treat a number of the multidrug-resistant isolates at the same time. 
     
       
         
           
               
             
               
                 TABLE 3 
               
             
            
               
                   
               
               
                 Relative susceptibility to different phage preparations; interpretation 
               
               
                 is generated from the data shown in FIG. 25. 
               
            
           
           
               
               
               
               
               
            
               
                   
                 
                   A. baumannii 
                 
                 
                   A. baumannii 
                 
                 
                   A. baumannii 
                 
                 
                   P. aeruginosa 
                 
               
               
                 Phage 
                 NCTC 13302 
                 ATCC 17978 
                 ATCC 17978 ColR 
                 PAO1 
               
               
                   
               
               
                 Phage Ab_1 
                 Susceptible 
                 Resistant 
                 Resistant 
                 Resistant 
               
               
                 Phage Ab_2 
                 Susceptible 
                 Susceptible 
                 Resistant 
                 Resistant 
               
               
                 Phage Pa_1 
                 Resistant 
                 Resistant 
                 Resistant 
                 Susceptible 
               
               
                   
               
            
           
         
       
     
       FIG.  25   . Data generated using bacterial impedance flow cytometry supporting the development of a susceptibility matrix for clinical isolates. A. Scattergrams showing the distribution of impedance measurements taken from individual bacteria of strains treated with phage Ab_1, Ab_2 and Pa_1 compared to control (no phage) after 90 minutes treatment. B. The data analysis shows both the total cell count and the cell count within the contoured region for each strain-phage combination. Either parameter can be important in demonstrating the susceptibility of particular strains to specific phage and both may be used in combination to further delineate the properties of the phage. Data is representative of at least 2 replicate experiments. 
     The data shows the ability to rapidly define the host specificity of different isolates to stocks of phage, such as might be held within a research facility in a hospital where they might 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, might be treated with phage cocktail preparations that include both Phage Ab_1 and Ab_2. Conversely a patient with an infection similar to ATCC 17978 would only be treated with Phage Ab_2. A phage-resistant bacterial isolate, such as strain ATCC 17978 CoIR (colistin resistant), which might be present in a patient or emerge during either antibiotic or phage therapy, would be recalcitrant to any of the phage tested. If the patient has an infection with a  P. aeruginosa  isolates similar to the reference strain PAO1, then this would likely respond to treatment with Phage Pa_1. 
     Example 2: Comparator Methods for Assessing Phage Susceptibility by Routine Microbiology 
     In the absence of the bacterial impedance flow cytometry platform, the susceptibility of a clinical strain to bacteriophage may be determined by classical microbiology methods. In such studies, plates containing well isolated bacteria (at time zero; TO), such as those from a clinical sample, are used to set up liquid culture of the strain of interest in TSB or LB, and grown overnight at 37° C. (approximately T18 h (hours)). These cultures are sub-cultured into fresh media and grown for around 1 hour (T19 h) and the bacteriophage are added. The bacteria-phage sample is then incubated under static conditions for at least 1 hour at 37° C. (T20). A top agar, containing TSB with 0.4-0.5% w/v agarose, supplemented with 10 mM MgSO 4 , is melted in a microwave and the temperature equilibrated to around 50° C. Approximately 4 ml of the top agar is added to the bacteria-phage suspension and suitable bacteria only and phage only controls and this is immediately poured over pre-warmed TSA or LB plate. After being allowed to set (approximately 1 hour; T21 h) the plates are inverted and incubated overnight (T˜36 h) to allow the 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 cleared or “hazy” plaques may indicate that the phage has integrated into the bacterial chromosome to form a temperate phage (prophage) infection. Microcolonies within the plaque may be indicative of the emergence of resistance during phage infection. Non-susceptible strains will show no plaque formation within the lawn of bacteria. 
     Aside from the length of time taken to assess susceptibility, typically ˜36 hours, the classical methods of determining phage susceptibility are labour intensive and accurately determining phage susceptibility may require significant training in viewing and interpreting the presence of plaques on plates. Similarly, identification of emergence of resistance to phage infection, may be challenging and open to interpretation. 
     Example 3: Assessment of Phage Susceptibility Using Bacterial Impedance Cytometry; Phage Cocktails 
     In a similar way to the matrix for individual phage susceptibility, described in example 1.3, phage cocktails generated by therapy companies or established from in-house stocks, could also be evaluated using bacterial impedance flow cytometry. The use of phage cocktails reflects the limited range of isolates of a single species which may be infected by a given phage; this is typically less than 50% of isolates for any given phage. A mixture of different phage, defined as a phage cocktail, may be used in this scenario to increase the number of clinical isolates which will be killed by the preparation. Typically a phage cocktail will be able to infect and kill in excess of 90% of clinical isolates from a particular target species, but not all isolates. The method is probably most effective where the end user/clinician has an initial bacterial ID to allow initial down selection of relevant phage cocktails, but this does not exclude the potential of using the method direct from clinical samples based on a presumptive diagnosis of likely pathogens in that sample (e.g.  Escherichia coli  or  Klebsiella pneumoniae  being likely causes of a complicated urinary tract infection). In this case, the bacterial isolate would be incubated with one or more phage cocktails, the cocktail itself consisting of 2 or more bacteriophage with different spectrums of activity against isolates of a different species. Such cocktails would be expected to have a wider combined coverage for infection and lysis of clinical isolates than the individual component phage. Optionally, the phage cocktails would be freeze dried or otherwise preserved in a microfluidic device or other reaction housing, such that the phage susceptibility assay could be automated with a bacterial impedance flow cytometry reader. The bacterial isolates would be prepared essentially as described in Example 1 and the bacterial suspension incubated with the phage on the device. After the appropriate incubation time, usually 90 minutes, the bacterial impedance measurement is made and the data analysed to give a simple read out on susceptibility to the phage cocktail. The metrics used could include a reduction in the overall cell count, a reduction in the number of bacteria within a contour within a reference profile, e.g. 95% of an untreated population, the migration of bacteria along the X-axis of the scatter plot indicative of a change in electrical radius (cell volume) and/or a migration on the Y-axis indicative of changes in the electrical opacity of the bacterial membrane (membrane permittivity). The assessment could be performed according to one or more of the assessment methods described earlier. This information may be used to trigger treatment for an infection or for one of the decolonisation approaches described in later examples, using the phage cocktail. 
     Optionally, the incubation between the phage cocktail and the bacterial isolate could be extended to evaluate the potential for resistance emergence during therapy. This could also be automated from the microfluidic device, such that the second analysis would be performed automatically following an extended incubation, such as after 8 hours. 
     Example 4: Workflow Detailing how a Bacterial Impedance Flow Cytometry Phage Susceptibility Assessment would be Used in the Clinic, Either with or without Prior Determination of Antibiotic Susceptibility 
     In current clinical practice, treatment with bacteriophage is only used in scenarios where there are no available antibiotics which could successfully treat an infection. This type of use is referred to as compassionate Phage Therapy (cPT) or emergency Investigational New Drug (eIND) use, but is increasingly common in situations where a patient is infected with an essentially untreatable infection 1-4 . The transition of phage therapy into a frontline treatment option is likely to occur in the future. This invention is a major improvement over current methods in supporting front line use of bacteriophage, as it enables a transition to rapid (&lt;4 hours) evidence-based, narrow-spectrum therapy for specific clinical indications. This “theranostic” style approach incorporates an element of bacterial identification, which could be using a technique for bacterial identification known in the art, or may be based on other factors such as the symptoms presented by the patient or the known clinical environment, assessed by phage lysis of the clinical isolate 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 microbiome, which would not be expected to alter significantly with a pathogen-directed therapy, compared to the wholesale changes and relatively indiscriminate killing which is known to occur with most antibiotic classes. 
     In either context, individual phage preparations or phage cocktails would be held within a treatment facility, such as a hospital microbiology laboratory and could be deployed for treatment of patients with non-resolving infections. One non-limiting example of the use of phage therapy is as follows
         a. A patient presents with an infection. Examples include (but are not limited to) a urinary tract infection, bacterial pneumonia, infection associated with an implanted device or sepsis.   b. A sample of body fluid is taken from the patient for routine microbiology assessment, for example antimicrobial susceptibility test and identification of the causative organism.   c. The patient is treated with one or more antibiotics recognised as standard of care, for example based on the NICE guidelines in the UK. These antibiotics fail to resolve the infection within 24 to 48 hours and the patient&#39;s condition continues to deteriorate   d. The microbiology results identify the species of bacteria, using a technique such as MALDI-TOF (Bruker, Biotyper) or gram stain or genetic analysis (such as DNA sequencing or DNA hybridisation or PCR). This information is available within approximately 12-16 hours post presentation, during which time the patient may be being treated as described in (c). The bacteria could 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,  Escherichia coli ), drug resistant  Neisseria gonorrhoea, Stenotophomonas maltophilia , or  Burkholderia cepacia/cenocepacia  complex.   e. The results of the antibiotic susceptibility test, if performed, informs the range of further treatment options available to the clinician. The data, utilising standard disk diffusion or broth dilution methodologies, demonstrates that the isolate is 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 has been shown to be multidrug/pandrug resistant, or based on the species identification, a phage susceptibility impedance assay is performed, essentially according to the method described in example 1. Results, available within 2 hours, identify that the clinical isolate is susceptible to the phage/phage cocktail and treatment is initiated.       

     The phage susceptibility impedance assay can be initiated once the bacterial ID has been completed, based on the presentation of the disease, clinical symptoms in the patient and known epidemiology of infections in the specific clinical setting. The phage susceptibility assay using impedance flow cytometry can be combined with a bacterial antibiotic susceptibility test performed using the same impedance analysis technique. This would allow determination of both antibiotic susceptibility and, if required, phage susceptibility of an isolate within around 4 hours. 
     The antibiotic susceptibility and phage susceptibility impedance assays can be combined to identify synergistic combinations of phage and antibiotics which would be highly effective at treating the infection. This type of interaction would not be identified by other means, such as the classical microbiology methods used for phage and antibiotic susceptibility measurements. Synergy between phage from any of the known phage families (including, but not limited to phage from the families Siphoviridae, Myoviridae, Podoviridae, Ackermannviridae, Inoviridae, Leviviridae, Microviridae, Cystoviridae) might be observed with any antibiotic (including, but not limited to, aminoglycosides, cephalosporins, penicillins, carbapenems, tetracyclines, polymixins, (fluoro)quinolones, oxazolidinones, macrolides, lincomycins, glycopeptides, sulphonamides, pleuromutilins) but particularly favourable synergistic interactions may be observed between lytic phage and antibiotics that do not generally penetrate Gram-negative bacteria (e.g. rifampicin, novobiocin, vancomycin, linezolid, fosfomycin). 
     A single type of phage or mixture of different phage can be used as a therapy and the phage susceptibility impedance assay can be used to monitor the efficacy of the treatment and to assess emergence of resistance to the treatment. 
     The impedance assay can be used to monitor the effectiveness of the phage therapy over time. The assay results could be used to inform on the efficacy of the therapy and to amend or modify the phage library dynamically to optimise the therapy, for example to take into account the emergence of resistance or further infections. 
     Example 5: Detection of Phage Sensitivity in Bacteria Directly in Clinical Samples; for Example, Detection of Urinary Tract Infections from Urine Samples 
     To facilitate rapid diagnosis of infection, bacterial impedance flow cytometry can be used directly on patient samples. One iteration of this approach is the direct measurement of phage susceptibility in for example urinary tract infections, pyelonephritis, or catheter-associated urinary tract infection (CAUTI) from a urine sample. The presumptive diagnosis in this case will be that the infection is caused by a species of Enterobacteriaceae, most commonly  E. coli, K. pneumoniae, Proteus mirabilis  and this diagnosis may be supported by local epidemiology and certain clinical symptoms (fever, leukocyte esterase positivity in urine). This enables a rapid phage susceptibility test to be carried out with phage/phage cocktails specific for each of these organisms. 
     The impedance assay can be used to determine an initial count to determine the level of bacteria in the urine sample, e.g. to comply with current clinical guidance defining a urinary tract infection on the basis of &gt;10 4  cfu/ml urine. If required, the urine sample can be diluted (for example with media, buffer, electrolyte or water, e.g. Tryptic Soy Broth TSB), Phosphate-buffered saline (PBS) or Mueller Hinton broth). The concentration after dilution can be approximately 5×10 5  cfu/ml. The sample is mixed with the phage or phage cocktail preparations, specific for each target species and the sample is incubated under conditions which are appropriate for the target bacteria (typically about 37° C. for 30 minutes under aerobic conditions, with or without shaking). The time of incubation might be for example in the region of 15-120 minutes but could be shorter or longer depending on the bacteria and phage. The time of incubation could be at least 10 minutes, or 15 minutes or more. 
     The results of the impedance phage susceptibility test allow the clinician to initiate treatment of the patient with the phage preparation either through systemic (intravenous) administration of the phage or via direct instillation of the phage into the urinary tract. Efficacy of treatment would be assessed on the basis of a number of different responses including a resolution of the patient&#39;s symptoms, reduction in cfu in the urine, reduction in secondary measures of infection such as leukocyte esterase, reduction in leukocyte count in the sample. 
     Optionally, the protocol might include a means of isolating or enriching the bacteria from urine prior to dilution to the correct starting concentration. This could be done at the Point of Care or in the clinic or testing laboratory. This might include, but is not limited to capture of bacteria on beads using physical-chemical or biochemical principles, for example poly cationic or poly anionic beads, beads coated with species-specific antibodies or generic bacteria capture ligands (e.g. mannose binding lectin, 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. 
     Example 6: Detection of Phage Susceptibility in Bacteria, Measured Directly in Clinical Samples; for Example, Blood and Other Sterile-Site Fluids 
     The concentration of bacteria in a clinical sample may be too low to allow direct measurement of phage susceptibility and the concentration of bacteria may need to be increased, for example by incubation, selective capture or filtration, to provide sufficient cells to determine phage susceptibility. Current standard of care for diagnosis of sepsis is based on culture, with blood samples taken from at least two independent sites on the body and cultured at 37° C. for the presence of either aerobes or anaerobes. A number of automated systems can be used to continuously measure the growth of any bacteria in blood. These include (but are not limited to) changes in the optical density of the sample, impedance changes of the sample, utilisation of oxygen, production of carbon dioxide, changes in the volatile gases within the head-space of growing cultures or other biophysical or biochemical or chemical methods. In each case, a positive blood culture identified by these methods might be expected to have a concentration of 10 3 -10 4  cfu/ml or greater. At these concentrations, it would be possible to analyse phage susceptibility directly. In order to execute the assay, the positive blood culture could be treated to remove cells (including red and white blood cells and platelets) through for example centrifugation, lysis of blood, filtration of cells or any other means. The blood sample could be mixed with a bacterial growth media and the phage susceptibility measured by impedance flow cytometry. The selection of phage panels for assessment might reflect the diverse range of organisms that are likely to cause sepsis. For example multiple phage cocktails might be tested for a susceptibility profile. Optionally, a rapid bacterial ID direct from blood bottle, such as the MBT Sepsityper IVD kit (Biotyper, Bruker), could be used to identify the pathogens in the positive blood culture prior to initiation of the phage susceptibility impedance protocol. 
     Optionally an additional step may be introduced to isolate or sub-culture the bacteria from the blood culture prior to analysis. This could be done at the Point of Care or in the clinic or testing laboratory. This might include, but is not limited to capture of bacteria on beads using physical-chemical or biochemical principles, for example poly cationic or poly anionic beads, beads coated with species-specific antibodies or generic bacteria capture ligands (e.g. mannose binding lectin, 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. 
     A similar approach might be used for other clinical samples such as cerebrospinal fluid (CSF), synovial fluid, or samples taken from wounds. Outgrowth and/or selective bacterial capture, can provide material which can be measured with impedance flow cytometry. 
     Example 7: Rapid Screening of Phage for Decolonisation Therapy; for Example for Cystic Fibrosis 
     The species-specific nature of bacteriophage can be used as the basis of narrow spectrum treatments for decolonisation. Such an approach may be utilised in chronic conditions where the acquisition or presence of particular species of bacteria are associated with particular elements of the pathology. Alternatively, phage therapy can be used where the presence of specific bacteria adversely affects the treatment options. This approach could be used for a wide range of chronic conditions in humans and animal. Table 4 shows non-limiting examples of these conditions along with the pathogen. 
     
       
         
           
               
             
               
                 TABLE 4 
               
             
            
               
                   
               
               
                 Examples of bacterial contributors to chronic disease, which would 
               
               
                 be therapeutic candidates for the use of targeted phage therapy. 
               
            
           
           
               
               
               
               
               
            
               
                   
                 Specific 
                   
                   
                   
               
               
                   
                 microbial 
                 Chronic disease 
                 Phage 
               
               
                 Pathogen(s) 
                 product 
                 exacerbation 
                 isolated? 
                 References 
               
               
                   
               
               
                 
                   Bacteroides fragilis 
                 
                 metalloprotease 
                 acute and chronic 
                 Yes 
                 5, 6 
               
               
                   
                 enterotoxin; 
                 intestinal disease in 
               
               
                   
                 
                   Bacteroides fragilis 
                 
                 children and adults 
               
               
                   
                 toxin 
               
               
                 
                   Enterococcus faecalis 
                 
                 exotoxin-secreting 
                 alcoholic hepatitis 
                 Yes 
                  7 
               
               
                 Enterobacteriaceae 
                 Colibactin 
                 Colorectal cancer 
                 Yes 
                  8-11 
               
               
                 ( E. coli   
               
               
                   Klebsiella pneumoniae ) 
               
               
                 
                   Fusobacterium nucleatum 
                 
                 Various 
                 Colorectal cancer 
                 Yes 
                 12-19 
               
               
                   
                   
                 and treatment failure 
               
               
                   
                   
                 for range of cancers 
               
               
                 
                   Klebsiella oxytoca 
                 
                 tilimycin and 
                 antibiotic associated 
                 Yes 
                 20 
               
               
                   
                 tilivalline 
                 hemorrhagic colitis 
               
               
                   
                   
                 (AAHC); 
               
               
                 gamma Proteobacteria (e.g. 
                 Trimethylamine 
                 Cadiovascular disease 
                 Yes 
                 21-23 
               
               
                   Acinetobacter baumannii , 
               
               
                   Klebsiella pneumoniae , 
               
               
                   Proteus mirabilis , 
               
               
                   Providencia  spp, 
               
               
                   Citrobacter  spp 
               
               
                 Gammaproteobacteria; (e.g. 
                 Cytidine 
                 Pancreatic cancer 
                 Yes 
                 24-26 
               
               
                   K. pneumoniae ) 
                 deaminase -long 
               
               
                   
                 form; capable of 
               
               
                   
                 deactivating 
               
               
                   
                 gemcitabine 
               
               
                   
                 and related 
               
               
                   
                 compounds 
               
               
                 
                   Pseudomonas aeruginosa 
                 
                 Various virulence 
                 Cystic fibrosis, 
                 Yes 
                 27 
               
               
                   
                 factors 
                 bronchiestasis and 
               
               
                   
                   
                 Chronic Obstructive 
               
               
                   
                   
                 Pulmonary Disorder 
               
               
                   
                   
                 (COPD) 
               
               
                   Stenotrophomonas maltophilia , 
                 Various virulence 
                 Cystic fibrosis 
                 Yes 
                 28 
               
               
                   Burkholderia cepacia / 
                 factors 
               
               
                   cenocepacia / multivorans , 
               
               
                   Achromobacter  spp. 
               
               
                   Pandoraea  spp and 
               
               
                   Ralstonia  spp 
               
               
                   
               
            
           
         
       
     
     For cystic fibrosis or other chronic lung conditions, one of a number of species of bacteria are associated with poor patient outcomes. These species could be targeted with bacteriophage therapy selected on the basis of impedance flow cytometry. The technique would be used to rapidly assess susceptibility, enabling prompt initiation of treatment. The assay could be provided in a high throughput format to facilitate screening against a number of species/strains. Target species might include, but are not limited to  Pseudomonas aeruginosa, Stenotrophomonas maltophilia, Burkholderia cepacia/cenocepacia/multivorans, Achromobacter  spp.  Pandoraea  spp and  Ralstonia  spp. 
     A non-limiting example of a test protocol is set out below. 
     Patient presents with cystic fibrosis or other chronic lung infection and has a sample collected e.g. of forced sputum or a bronchiolar alveolar lavage (BAL). 
     Optionally, the sample might be assessed using routine microbiology methods, with bacterial cultured using selective media to enrich for a species of interest and if required identification of species. 
     The BAL sample is mixed with growth media and the sample incubated with either single phage isolates or a phage cocktail for a certain period of time (typically 30-120 minutes but could be shorter or longer). 
     Other examples include dispensing the phage or phage cocktails in a 96-well plate, covering a range of different species and with phage preparations showing different species selectivity. This can be interfaced with the bacterial impedance assay using a range of liquid handling systems. 
     The susceptibility of the clinical isolate to the phage or phage cocktail is determined using impedance flow cytometry. If the assay is performed directly on BAL samples, one or more phage preparations would affect one or more pathogen within the samples. This would be indicated by a change in the electrical properties associated with a change in the physico-chemical properties of the bacteria. 
     One or more phage or phage cocktail would be used for decolonisation of the patient, to significantly reduce or eradicate high consequence pathogens that adversely affect health in chronically infected patients. This is commonly used for CF patients on first presentation with  Pseudomonas aeruginosa , but would be appropriate for a range of pathogens. 
     In an alternative assay, phage-based eradication therapy could be combined with one or more antibiotics. An example of an eradication therapy that would benefit from the inclusion of a selected phage is a combined treatment of nebulised colistin with oral ciprofloxacin for 3 months. 
     Impedance cytometry could be used to monitor the success of eradication therapy, by following changes in susceptibility to phage over time. This information could be used to amend the phage library to address changes in colonisation or emergence of resistance. 
     Example 8: Identification of Phage for Gut Decolonisation Treatment 
     There is growing awareness of the importance of gut colonisation in the development of a range of chronic diseases; a non-exhaustive list of examples is outlined in Table 4. It is not currently possible to selectively remove particular pathogens from the gut, using even narrow spectrum antibiotics, as they do not have sufficient selectivity. Phage treatment to selectively decolonise the gut or other microbiomes is a potential solution to these challenges, but it depends on the availability of techniques that allow rapid and high throughput screening of phage/phage cocktails. Bacterial impedance flow cytometry is an example of such a technology, allowing both rapid and high throughput identification of phage susceptibility as the basis for selective treatment. A workflow that would be suitable for this approach is identified below. 
     a. A stool sample is collected from a patient exhibiting symptoms associated with a wide range of chronic conditions, represented by the non-exhaustive list provided in Table 4.
 
b. The sample is cultured on selective plates to enrich for the target pathogen which is the target for phage-based elimination therapy. The bacteria are suspended in bacterial growth media and incubated with the phage/phage cocktails for a predetermined period of time.
 
c. The susceptibility of the target organisms to specific phage preparations is determined using the bacterial impedance flow cytometry method. The phage(s) that are effective against the particular target strain, carried 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 gut. Alternatively the phage preparation is delivered directly to the small or large intestine or other locations in the GI tract.
 
d. The efficacy of the phage-based elimination therapy can be assessed by repeated fecal sampling and selective culture to monitor for the presence of the pathogen or the replacement of strains manufacturing toxic/harmful gene products with more benign strains.
 
e. Optionally the phage-based elimination therapy may be carried out in conjunction with the therapeutic use of one or more probiotic.
 
f. Optionally, the phage-based elimination therapy is a precursor for subsequent therapy to treat the underlying chronic condition, as might be the case for selective elimination of particular species (e.g.  K. pneumoniae ) expressing a form of cytidine deaminase prior to cancer therapy using compounds such as gemcitabine. This form of the enzyme deactivates the chemotherapy drug reducing its activity and, as such elimination therapy potentially improves treatment outcomes for various pancreatic and lung cancers.
 
     Example 9: Pre-Treatment of Fecal Transplant Material to Eliminate Pathogens Associated with Chronic Disease 
     Fecal transplantation has proved to be a highly effective treatment for recurrent bouts of disease caused by  Clostridium difficile  and is now being explored for a range of other chronic conditions, including, but not limited to Enterocolitis 29 , chronic liver disease 30  and irritable bowel disease 31 . In a similar way to the example detailing selective elimination of problematic bacteria from the gut, a similar phage-based elimination approach can be used with fecal transplant material prior to transplantation into the large intestine. This obviates the potential problems associated with re-introducing bacteria which cause chronic disease, which has been associated with adverse outcomes 32 . Whilst this can be achieved in some cases by screening, the ability to selectively eradicate the problem bacteria increases the flexibility and efficacy of the fecal transplantation approach. 
     The workflow is essentially the same as for the gut elimination example described above (Example 8), except that the fecal material is handled ex vivo and treated with phage selected to eliminate specific bacterial species, prior to transplantation. 
     Example 10: Treatment of an Infection where Phage Delivery of a Resistance Breaker is Essential to Mediate Susceptibility to an Antibiotic 
     Phage are increasingly being used as delivery vehicles for a range of antimicrobial agents and antibiotic resistance breakers, where expression of a gene is required within the bacteria. Examples for genetically encoded antibacterial agents might include Small, Acid-soluble Spore Protein 33 , transcription factor decoys 34  and various antibiotic resistance breakers, such as beta-lactamase inhibitors, modulators of efflux pump expression. The efficacy of these molecules as antimicrobials is dependent on the ability of the phage to infect the target species and, as such, there remains a need to rapidly determine phage susceptibility. 
     One example of a method is as follows: A clinical isolate from an infection site is mixed with either the genetically engineered phage carrying the antimicrobial gene or with the base phage which is the basis for the delivery vector. The incubation of the phage with the target is carried out as discussed previously, and the bacterial impedance measured and analysed. Results indicative of either phage-mediated lysis are analysed as seen previously. The time to expression of the antimicrobial gene, may mean that the rapid assay format does not measure the effects of the gene expression. If it does contribute then the impedance measurement will also reflect the gene-based antimicrobial effect. Optionally, the effects of genes which impact on antibiotic resistance, will only be exerted in the presence of the antibiotic and the phage-mediated infection. 
     Example 11 
     1. The Use of Serum Bactericidal Assays in Clinical Settings 
     Serum bacteridical assays are used to assess the ability of a patient&#39;s blood to kill a pathogen of interest. These may be used in a range of assays to assess either naturally occurring antibody levels or antibodies generated by either active (vaccination) or passive (immunotherapy with pre-formed antibodies) immunisation. This activity forms an integral part of a patient&#39;s protection against a pathogen and will often work in conjunction with other treatments (e.g. antibiotic, phage). This type of measurement may be particularly important in settings where the infection may be in a wound which is not in the periphery, such as might be observed in endocarditis, meningitis, prosthetic joint infection or osteomyelitis. Similarly, it might be important to measure these types of activity in infections in neutropenic or other immunocompromised patients. 
     Although these are valuable assays in the context of antibody mediated killing, they are not routinely used in a clinical setting as a primary read-out. This reflects the difficulty in performing these assays and lack of standardised methods that can provide real-time data (ie not dependent on external laboratory analysis. The culture-based laboratory analysis for the presence and enumeration of viable bacteria, typically over 24 hours but potentially up to 48-72 hours for slow growing species, also limit the usefulness of the method. The assay measures the lowest dilution of the patient&#39;s sera which will adequately kill the target pathogen causing an infection and is often expressed as a dilution factor (e.g. 1:8, 1:16) Optionally, the efficacy of the serum bactericidal assay may be used to assess combinations of antibiotic and serum killing, where antibiotic is added to the serum at a defined concentration prior before the assay being carried out. This conceptually supports the development and use antibiotics that work in a complementary way to antibody-mediated killing. 
     The bacterial impedance flow cytometry assay can be used to measure serum bactericidal activity, rapidly and in a near-patient setting to support clinical decision making. A workflow that might be used with the assay in a clinical setting is laid out below.
         a. A patient presents at a clinic with an infection related, for example, to potential endocarditis, following cardiac surgery. The pathogen causing the infection is identified through either culture based or molecular methods. The pathogen may be one of a range of pathogens, including but not limited to,  Staphylococcus  species,  Streptococcus  species or  Enterococcus  species.   b. A culture of the pathogen is prepared in cation adjusted Mueller Hinton Broth by picking 3 colonies from a plate. The concentration of bacteria is corrected to approximately 5×10 5  cfu/ml.   c. The bacteria are added to an equal volume of patient serum diluted in standard ultrafiltered human serum and the bacteria/sera is incubated for 1 hour at 37° C. in the presence of 5% CO 2 .   d. The sample is assessed using the bacterial impedance assay, which measures both the number of viable bacteria in the sample and any changes in impedance profile that might indicate serum-mediated bacterial lysis prior to killing. Comparison of the sample with an untreated bacterial population would also allow the identification of antibody binding.   e. The serum titre which kills &gt;99.5% of the bacteria in the sample may be indicative of likely clinical outcomes; a patient with a high peak titre (e.g. 1:32 dilution positive for killing at the required rate) being more likely to be able to clear the infection than a patient with a low peak titre (e.g. 1:2 dilution or higher). The information could be used to revise therapeutic options or look at options for surgical intervention.   f. Optionally, the method could be used to monitor the efficacy of a vaccination programme, aimed at increasing the serum concentration of antibodies for a particular pathogen to generate protective bactericidal antibody responses. In this case, serum samples from patients pre- and post-vaccination are serially diluted and incubated with the target pathogen as described above. The bacterial impedance flow cytometry assay is performed and the number of viable cells quantified. An increase in the antibody titre post-vaccination would correlate with a satisfactory kill being achieved with a higher dilution of the patient serum (e.g. 1:128 compared to 1:8 pre-vaccination).   g. Optionally, the bacterial impedance flow cytometry method would provide a rapid readout allowing the monitoring of serum levels for a passively administered antibody, therapy targeting a multidrug resistant pathogen (e.g. for  P. aeruginosa   35 ). In this case, the method described above would be used to optimise the dosing of the monoclonal antibody product, to ensure that the serum dilution that effectively kills the target strain, is maintained above a pre-defined threshold. This ensures that there is sufficient circulating antibody to effectively minimise the spread of the bacteria and/or to prevent the cytotoxicity caused by the production of any toxins or endotoxins by the bacteria.       

     Example 12: Determining the Efficacy of Membrane Penetrating Peptide Antimicrobials Effecting Bacterial Killing Using Bacterial Impedance Flow Cytometry Method 
     Antimicrobial peptides (sometimes referred to as host-defence peptides), bacteriocins, lanthipeptides, pyocins, phage-derived endolysins, endopeptidases and muralytic proteins (e.g. Artilysins) have all been proposed as candidates for the development of new antimicrobial agents. Many of these biologics have narrow spectrums of activity and can be tailored to be specific for certain species of bacteria, rather than having broad spectrum activity that potentially damages the microbiome. As this is often akin to the way in which phage therapies are used, there are natural synergies with the bacterial impedance flow cytometry method. 
     The method for determining the efficacy of different membrane penetrating peptide antimicrobials is essentially the same as for Example 1. Briefly, colonies are picked from plate carrying bacteria from a clinical sample (e.g. a urine sample from suspected UTI) into Tryptone soy broth (TSB) and incubated for 30 minutes prior to addition of the membrane penetrating peptide antimicrobial preparation. The incubation is typically carried out at 37° C. with shaking. The bacteria are diluted to a concentration of approximately 5×10 5  cfu/ml in TSB and representative examples of cationic antimicrobial peptides (cAMP), e.g. pleurocidin and alpha-helical pore forming peptides (melittin) are added. The concentrations are selected to span the minimum inhibitory concentration of the two strains, as might be used clinically for an antimicrobial breakpoint determination. Optionally, the bacterial impedance flow cytometry method may be used to generate a measurement of the minimum inhibitory concentration or a fixed concentration is used on the basis of a resistant/susceptible breakpoint. The sample is incubated at 37° C. for 30 or 60 minutes in a static incubator at 37° C. The population at each timepoint is analysed using bacterial impedance flow cytometry and the data collected and analysed to measure both the viable cell number and any migration of the cell population out of a contour enclosing a percentage of a control or untreated population of the same species. 
     Both peptides tested generate a rapid bactericidal kill, resulting in &gt;5-log reduction in viable count within 4 hours, through membrane disruption (both peptides) and interaction with one or more intracellular target (cAMP only). At the time points measured it is possible to identify a time-dependency in the number of bacteria that remain within the contour, with a migration in the scatterplot consistent with membrane disruption caused by the peptides. This clearly differentiates the response of the populations to the high and low concentrations of peptide used in the study, which is consistent with the relative susceptibility of the bacteria to the two peptides. 
     If used in a clinical setting, this would allow the rapid determination of the susceptibility of a strain causing an infection and provide information to direct therapy with these peptides. 
       FIG.  26    shows that different types of antimicrobial peptide cause a rapid change in the bacterial impedance at supra- but not sub-inhibitory concentrations. Two different types of antimicrobial peptide, a cationic AMP (cAMP; membrane penetrating peptide, a D-amino acid version of pleurocidin from winter flounder) and an alpha helical peptide (melittin; pore forming peptide) were incubated with  Escherichia coli  (NCTC 12923) and  Klebsiella pneumoniae  (NCTC 13368), at a 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) concentration, for 30 or 60 minutes. The bacterial impedance of the population was measured. The scattergrams show a rapid migration of the bacteria out of the contour defined by the untreated population, within 30 minutes with both peptides and species tested, at the supra-inhibitory but not the sub-inhibitory concentration. NCTC 13368 shows a lower susceptibility to melittin than NCTC 12923 but results are comparable for the cAMP at the concentrations tested. The results are typical of at least two experiments carried our independently. The various embodiments described herein are presented only to assist in understanding and teaching the claimed features. These embodiments are provided as a representative sample of embodiments only, and are not exhaustive and/or exclusive. It is to be understood that advantages, embodiments, examples, functions, features, structures, and/or other aspects described herein are not to be considered limitations on the scope of the invention as defined by the claims or limitations on equivalents to the claims, and that other embodiments may be utilised and modifications may be made without departing from the scope of the claimed invention. Various embodiments of the invention may suitably comprise, consist of, or consist essentially of, appropriate combinations of the disclosed elements, components, features, parts, steps, means, etc., other than those specifically described herein. In addition, this disclosure may include other inventions not presently claimed, but which may be claimed in the future. 
     Example 13 
       A. baumannii  (NCTC 13302) was incubated with phage essentially as described in Example 1 with the exception that a multiplicity of infection (MOI) of 0.01, 0.1, or 1 was used. Bacterial impedance flow cytometry profiles were measured for an untreated sample and treated samples every 30 minutes for 2 hours.  FIG.  27    shows bacterial impedance flow cytometry profiles for  A. baumannii  (NCTC 13302) for a sample, untreated or treated with Phage, 2 hours after treatment. Scatterplots show the distribution of the impedance measured for individual bacteria in the untreated sample (A, MOI=0), and a sample treated with an MOI of 1 (B), 0.1 (C) or 0.01 (D). A contour was calculated which encompassed 50% of the untreated population at each timepoint. The number of individual bacteria within this contour was counted for each MOI (0, 0.01, 0.1, 1).  FIG.  28    shows the variation in cell count compared to an untreated population of cells (black) for populations treated with an MOI of 1 (dark grey), an MOI of 0.1 (mid grey) and an MOI of 0.01 (light grey) at time points of A: 30 mins; B: 1 hour; C: 1 hour 30 mins; D: 2 hours. Whilst populations inoculated with an MOI of 1 show a decrease at each time point, populations inoculated with an MOI of below 1 initially decrease slightly relative to the untreated population and then return to at least the level of the untreated population. 
     Example 14: Assessment of Resistance Emergence to Either Phage or Antimicrobial Peptides 
     A key component in deciding about the suitability of a phage or phage cocktail for treatment of a bacterial isolate, is an assessment of whether resistance is likely to emerge rapidly during treatment and adversely affect the treatment outcome. 
     In this case, a clinical isolate of bacteria is incubated with phage essentially as described in Example 1. An initial assessment of phage susceptibility may be made within 90 minutes or 120 minutes, for rapidly growing bacteria and phage with a short latent period. By continuing to assess the bacterial impedance flow cytometry values over an extended period of time, in this case measuring the impedance profile hourly up to 6 hours, and comparing the data with the initial readings, it is possible to see whether there is a subset in the population of bacteria which remain in the gated region identified from a control, untreated or reference population. If the number of bacteria in this contour increases, despite the generation of new progeny phage and rounds of re-infection, this is likely to be indicative of mutations leading to resistance that would make the choice of this phage for treatment unsafe. A similar effect is observed e.g. in Example 13 when a low multiplicity of infection of phage (MOI &lt;1) is administered and the number of bacteria in the gated region increases after an initial decrease. 
     This resistance emergence is evident on a single bacteria level analysis, such as impedance flow cytometry, at a much earlier point than can be achieved with other techniques. This allows more precise and timely decisions about suitability of phage for treatment to be made. 
     It is possible to simulate this situation of natural phage resistance emergence by spiking in low frequencies of resistant phage into a generally susceptible population of the same strain. 
     Similar approaches may be taken to assess emergence of resistance to antimicrobial peptides, by serially sampling bacterial populations treated as in Example 12, over 4-6 hours. This again would help make decisions about treatment strategy for particular clinical isolates and presentations. 
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