Bacteria classification and analysis

Abstract

In addition to a variety of other antimicrobial agents or mixtures, bacterial cells in a biological sample are exposed to a test antimicrobial agent. The MIC value of the test antimicrobial agent is determined based on the phenotypic signature response of the bacterial cells to the test antimicrobial agent. The bacterial cells are classified based on their respective phenotypic signature responses to other antimicrobial agents or mixtures and the classification is used to determine the CBP value of the test antimicrobial agent. MIC and CBP values are then determined and can be used to determine whether bacterial cells in the biological sample are sensitive to the test antimicrobial agent.

Description

Technical Field

[0001] The present invention relates generally to bacterial classification and analysis. Technical Background

[0002] Antibiotic susceptibility testing (AST), also known as antibiotic sensitivity testing, is a measurement of bacterial susceptibility to antibiotics. Susceptibility test results allow clinicians to select an appropriate antibiotic or mixture of antibiotics based on knowledge of the disease-causing bacteria and their susceptibility and resistance.

[0003] The original AST method was a phenotypic method involving exposure of bacteria to antibiotics on agar plates or diluted in agar or broth. Such phenotypic methods include the disc diffusion method, also known as the Kirby-Bauer method, in which bacteria are cultured on agar plates and bacterial growth near the antibiotic-impregnated disc is observed. If the antibiotic inhibits microbial growth, a clear circle or inhibition zone will be seen around the disc. Then, by comparing the diameter of the inhibition zone with a defined threshold (related to the minimum inhibitory concentration (MICs)), the bacteria are classified as sensitive, moderate or resistant to the antibiotic. Other phenotypic methods include gradient methods, such as the Etest, which uses plastic strips impregnated with different concentrations of antibiotics placed on agar and observes bacterial growth after a period of incubation. The MIC can be identified based on the intersection of the teardrop-shaped inhibition zone with the mark on the strip.

[0004] The main disadvantage of the phenotypic methods exemplified above is that they usually require at least overnight bacterial culture to obtain a visible reaction. Therefore, it takes a relatively long time before the AST results are available. Another disadvantage is that only a single antibiotic or a small amount of antibiotics are usually tested in a single AST test.

[0005] Another group of AST methods are genetic methods based on polymerase chain reaction (PCR), deoxyribonucleic acid (DNA) microarrays or DNA chips. These genetic methods do not examine the phenotypic response of bacteria to antibiotics, but analyze whether the bacteria have genes that confer antibiotic resistance. Genetic methods have the advantage of surpassing culture-based phenotypic methods in that they are faster. Disadvantages include the need for knowledge of the resistance gene to be tested, expensive, and usually requiring specially trained personnel. In addition, sometimes the genotypic profile of the resistance gene detected does not always match the resistance profile seen by the phenotypic method.

[0006] Microfluidic devices and chips have been proposed for rapid and parallel monitoring of bacterial phenotypic responses to a panel of antibiotics. Microfluidic-based AST is rapidly developing and does not suffer from the drawbacks associated with many genetic approaches.

[0007] Wang et al., Current Biology 2010, 20: 1099-1103 disclose a prior art microfluidic device called a “mother machine.” The mother machine allows for the monitoring of cells in multiple different cell channels in parallel.

[0008] U.S. Patent Nos. 10,041,104; 10,570,437; and 10,913,969 show further microfluidic devices useful for analysis of biological samples.

[0009] Baltekin et al., PNAS 2017, 114(34):9170-9175 discloses a rapid antibiotic susceptibility testing (AST) test (FASTest) using a microfluidic device.

[0010] U.S. Patent No. 8,828,680 discloses an automated assay method and system for determining microbial sensitivity and microbial identification by using a hybrid system combining turbidity and fluorescence assays. The test system includes a plurality of reaction chambers for performing biochemical tests. Each reaction chamber is configured to receive or contain one or more test reagents, including a substrate for at least one enzyme unique to a microbial family, genus, and / or species. If the enzyme acts on the substrate, a detectable product is formed that is associated with the identity of the microorganism in the sample.

[0011] There remains a need for efficient classification and analysis of bacterial cells, such as classification and analysis useful in connection with antimicrobial susceptibility testing. Summary of the invention

[0012] One overall purpose is to be able to classify bacteria.

[0013] Another goal is to be able to analyze bacterial cells to determine minimum inhibitory concentrations and clinical breakpoint values.

[0014] These and other objects are met by the embodiments disclosed herein.

[0015] The invention is defined in the independent claim. Further embodiments are defined in the dependent claims.

[0016] One aspect of the present invention relates to a method for classifying bacteria. The method comprises exposing bacterial cells in a biological sample to a first antimicrobial agent or mixture, and exposing the bacterial cells in the biological sample to (i) a second antimicrobial agent or mixture, and / or (ii) a salt or a salt mixture. The method further comprises classifying the bacterial cells in the biological sample based at least on (i) the phenotypic characteristic response of the bacterial cells to the first antimicrobial agent or mixture, and (iia) the phenotypic characteristic response of the bacterial cells to the second antimicrobial agent or mixture and / or (iib) the phenotypic characteristic response of the bacterial cells to the salt or salt mixture.

[0017] Another aspect of the present invention relates to a method for bacterial analysis. The method includes exposing bacterial cells in a biological sample to a test antimicrobial. The method also includes classifying the bacterial cells based on the above-mentioned bacterial classification method. The method further includes determining a clinical breakpoint (CBP) of the test antimicrobial based on the classification results of the bacterial cells. The method also includes determining the minimum inhibitory concentration (MIC) of the test antimicrobial based on the phenotypic characteristic response of the bacterial cells to the test antimicrobial. The method also includes comparing the MIC with the CBP.

[0018] A further aspect of the invention relates to an analyzer comprising a pressure source configured to apply pressure to a microfluidic device; a processor; and a memory comprising instructions executable by the processor to cause the processor to control the pressure source to expose bacterial cells in a biological sample to a first antimicrobial agent or mixture in the microfluidic device and to control the pressure source to expose bacterial cells in the biological sample to (i) a second antimicrobial agent or mixture and / or (ii) a salt or salt mixture in the microfluidic device. The processor also classifies bacterial cells in the biological sample based on at least (i) a phenotypic characteristic response of the bacterial cells to the first antimicrobial agent or mixture, and (iia) a phenotypic characteristic response of the bacterial cells to the second antimicrobial agent or mixture and / or (iib) a phenotypic characteristic response of the bacterial cells to the salt or salt mixture.

[0019] Other aspects of the present invention also relate to an analyzer, comprising a pressure source configured to apply pressure to a microfluidic device; a processor; and a memory comprising instructions executable by the processor, so that the processor controls the pressure source to expose bacterial cells in a biological sample to a test antimicrobial in the microfluidic device, controls the pressure source to expose bacterial cells in the biological sample to a first antimicrobial or mixture in the microfluidic device, and controls the pressure source to expose bacterial cells in the biological sample to (i) a second antimicrobial or mixture and / or (ii) a salt or salt mixture in the microfluidic device. The processor also classifies the bacterial cells based on at least (i) a phenotypic characteristic response of the bacterial cells to the first antimicrobial or mixture, and (iia) a phenotypic characteristic response of the bacterial cells to the second antimicrobial or mixture and / or (iib) a phenotypic characteristic response of the bacterial cells to the salt or salt mixture. The processor further determines the CBP of the test antimicrobial based on the classification results of the bacterial cells and determines the MIC of the test antimicrobial based on the phenotypic characteristic response of the bacterial cells to the test antimicrobial. The processor also compares the MIC to the CBP.

[0020] The present invention allows the classification of bacterial cells in a biological sample, and this classification can be used to determine the CBP of the bacterial cells and the antimicrobial agent. The present invention also allows the determination of the CBP simultaneously with the MIC determination of the antimicrobial agent. Therefore, the present invention can verify whether the antimicrobial agent is clinically effective in treating a bacterial infection caused by bacterial cells in a patient. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The embodiments, together with further objects and advantages, may be better understood by referring to the following description and accompanying drawings, in which:

[0022] Figure 1 Schematic illustration of the MIC-based classification of sensitive (S), resistant (R), and intermediate (I) phenotypes based on clinical breakpoints from epidemiological studies.

[0023] Figure 2 is a flow chart illustrating a method for classifying bacteria according to an embodiment.

[0024] Figure 3 To illustrate the embodiment according to Figure 2 Flow chart of the sub-circuit of the classification step S5 in .

[0025] Figure 4 To illustrate the embodiment according to Figure 3 Flowchart of determining sub-circuits of Gram classification step S10.

[0026] Figure 5Schematically illustrates the embodiment according to Figure 3 The sub-circuit of the Gram classification step S10 is determined in FIG.

[0027] Figure 6 Schematically illustrates the embodiment according to Figure 3 The subroutines belonging to the classification step S11 and the classification step S12 are determined.

[0028] Figure 7 To illustrate the embodiment according to Figure 3 Flowchart of determining sub-circuits of Gram classification step S10.

[0029] Figure 8 To illustrate the embodiment according to Figure 3 Flow chart of the sub-circuit of determining the category classification step S11.

[0030] Fig. 9 To illustrate the embodiment according to Figure 3 Flowchart of the sub-circuit of classification step S12.

[0031] Figure 10-13 Schematically illustrates various embodiments Figure 1 The sub-circuit of the classification step S6.

[0032] Fig.14 The present invention is a flow chart illustrating a method for analyzing bacteria according to an embodiment.

[0033] Fig.15 According to the implementation plan Fig.14 Flowchart of additional optional steps of the illustrated method.

[0034] Fig.16 Schematic illustration of the dose-response curves for bacterial cells exposed to different concentrations of antibiotics.

[0035] Fig.17 Schematically illustrates the Fig.16 The correlation between the effect concentration and the reference MIC value was determined by the dose-response curve.

[0036] Figures 18A to 18C Schematic illustration of a microfluidic chip attached to a chip carrier (18A, 18B) and a bottom view of the microfluidic chip attached to the chip carrier (18C).

[0037] Fig.19 The arrangement of the microfluidic chip and the chip carrier in the substrate is schematically illustrated.

[0038] Fig. 20 The microfluidic device is schematically illustrated.

[0039] Fig.21 is an overview of a set of cell channels in a microfluidic device connected to a processor configured to control fluid flow in a fluid circuit of the microfluidic device.

[0040] Fig. 22 The operational details of the microfluidic device in which bacterial cells flow into the cell channel during the capture process are illustrated.

[0041] Fig.23 It is a phase contrast microscopy image of bacterial cells trapped in a cell channel (the darker part represents the cell, and the lighter part represents the empty part of the cell channel), with a magnification of 100 times.

[0042] Fig.24 An analyzer configured to implement a method according to an embodiment is schematically illustrated.

[0043] Fig.25 A block diagram illustrating an embodiment of an analyzer is shown.

[0044] 26 illustrates the Gram classification ( 26A ) of biological samples (N=676) as Gram-positive or Gram-negative and the genus classification ( 26B, 26C ) of biological samples (N=130). Specific implementation plan

[0045] Throughout the drawings, the same reference numerals are used for similar or corresponding elements.

[0046] The present invention relates generally to bacterial classification and analysis.

[0047] The traditional method of determining whether an antimicrobial such as an antibiotic is effective in treating an infection of a particular bacterial strain is to compare the minimum inhibitory concentration (MIC) of the antimicrobial determined for the particular bacterial strain with the clinical breakpoint (CBP) of the antimicrobial determined for the bacterial group covering the particular bacterial strain. In short, if the MIC is lower than the CBP, the bacterial strain is classified as susceptible to the antimicrobial, and if the MIC is higher than the CBP, the bacterial strain is classified as resistant to the antimicrobial.

[0048] MIC is the lowest concentration of an antimicrobial that prevents visible growth of a bacterial strain or isolate. Traditionally, MIC values ​​are determined by antibiotic susceptibility testing (AST), such as broth dilution test or Etest. However, the MIC value determined by AST does not itself define whether an infection caused by a bacterial strain or isolate is likely to be treatable with an antimicrobial in a patient. Clinically, a more relevant therapeutic value is the so-called CBP. CBP is the concentration of an antimicrobial used to define whether an infection caused by a specific bacterial strain or isolate is likely to be treatable in a patient. Typically, these are defined as sensitive or resistant to antimicrobials. CBP concentrations differ from antimicrobial susceptibility tests because they take into account what happens to the antimicrobial in the body, pharmacology and pharmacokinetics, which all affect the clinical efficacy of the antimicrobial.

[0049] CBP is defined and listed according to the order, genus or species of bacteria. Therefore, in order to determine whether an infection caused by a specific bacterial strain or isolate is treatable with an antimicrobial, it is not only necessary to determine the MIC of the antimicrobial to the bacterial strain or isolate, but also to determine the order, genus or species of the bacterial strain or isolate. Information on the order, genus or species is needed so that the correct CBP can be selected to compare with the determined MIC to verify whether a specific bacterial strain or isolate is classified as sensitive or resistant. Therefore, in the prior art, two different analyses are needed, AST is used to determine the MIC, and another analysis is used for the identification of the order, genus or strain, such as using morphological tests, biochemical tests, serotyping and / or genetic tests.

[0050] The present invention is capable of determining both the MIC value of a test antimicrobial agent and the identification or classification of a bacterial strain or isolate required for CBP in a single assay, typically in a microfluidic device. Thus, a single device and assay can be used to provide the information needed to determine whether a patient infection caused by a particular bacterial strain or isolate is likely to be treatable (sensitive) or untreatable (resistant) using a test antimicrobial agent.

[0051] Typically, CBP is defined as an order / genus / species related antimicrobial concentration value that facilitates the interpretation of phenotypic sensitive / resistant (S / R) profiles based on MIC values. Thus, bacterial strains or isolates with MIC values ​​less than or equal to the sensitive CBP value are considered sensitive (S), otherwise resistant (R). In some cases, in order to distinguish between intermediate (I) phenotypes, a resistant CBP is also defined, see Figure 1CBP is provided and updated annually by specialized bodies, such as the European Committee on Antimicrobial Susceptibility Testing (EUCAST) in Europe and the Clinical Laboratory Standards Institute (CLSI) in the United States.

[0052] Another key parameter value is represented by the epidemiological cutoff value (ECOFF), which is the highest MIC value of bacteria without any resistance mechanism selection (i.e., wild-type (WT) bacteria). ECOFF is very useful for evaluating the intrinsic resistance of certain species to specific antibiotics and for establishing CBP.

[0053] Figure 1 Examples of MIC distributions and ECOFF value determinations from the EUCAST epidemiological study involving thousands of strains or isolates of a specific bacterial species exposed to antimicrobial agents are illustrated.

[0054] As used herein, "biological sample" includes any sample containing bacterial cells, preferably a fluid sample, more preferably a liquid sample. The biological sample is preferably a body fluid sample, such as a body fluid sample obtained from a patient, including a processed body fluid sample obtained from a patient. Illustrative but non-limiting examples of such body fluid samples include urine, blood, plasma, serum, amniotic fluid, cerebrospinal fluid, lymph, saliva and synovial fluid. Alternatively, the biological sample can be a biological sample obtained from a solid body sample (such as a biopsy), wherein the bacterial cells of the solid body sample have been suspended or dispersed in a fluid (preferably a liquid, such as a culture medium).

[0055] As used herein, "antimicrobial" refers to any molecule, compound, composition or other agent that kills bacterial cells or stops or at least reduces bacterial cell growth. Typical but non-limiting examples of such antimicrobial agents include drugs or agents comprising drug candidates, such as antibiotics or other antibacterial agents. Exemplary but non-limiting examples of such antibiotics include penicillins, cephalosporins, polymyxins, rifamycins, lipiarmycins, sulfonamides, lincosamides, beta-lactams, macrolides, quinolones, tetracyclines and aminoglycosides.

[0056] Figure 2 is a flow chart illustrating a method for bacterial classification. Bacterial classification can be implemented as a stand-alone method or process to classify bacterial cells in a biological sample to determine the order or genus of the bacterial cells. The classification of bacterial cells is advantageously used as a basis for determining or selecting the CBP of bacterial cells. In this case, bacterial classification can be part of an analytical process or method and will be referred to herein. Fig.14 Further disclosure.

[0057] Figure 2 In the method of bacterial classification, the method includes exposing the bacterial cells in the biological sample to a first antimicrobial agent or mixture in step S1. Step S2 correspondingly includes exposing the bacterial cells in the biological sample to (i) a second antimicrobial agent or mixture and / or (ii) a salt or a salt mixture. Then, the bacterial cells in the biological sample are classified in step S5 based on at least (i) the phenotypic characteristic response of the bacterial cells to the first antimicrobial agent or mixture, (iia) the phenotypic characteristic response of the bacterial cells to the second antimicrobial agent or mixture, and / or (iib) the phenotypic characteristic response of the bacterial cells to the salt or the salt mixture.

[0058] Steps S1 and S2 can be performed in any order in succession, but are preferably performed at least partially in parallel. In this latter preferred case, bacterial cells in the biological sample are exposed to a first antimicrobial agent or mixture, and other bacterial cells in the biological sample are exposed to a second antimicrobial agent or mixture and / or other bacterial cells in the biological sample are exposed to a salt or salt mixture.

[0059] As an example of such concurrent exposure to multiple, i.e., at least two, antimicrobial agents or mixtures, a biological sample containing bacterial cells is loaded into the cell channel 140 of the microfluidic chip 10, see Figures 18A-18C , Fig.21 The microfluidic chip 10 includes a plurality of groups 130 of cell channels 140, a plurality of input channels 110, and a plurality of output channels 120. Fig.21 As more clearly shown in FIG. 1 , each input channel 110 is in fluid communication with a respective output channel 120 via a cell channel 140 of a respective set 130 of cell channels 140. The cell channels 140 include respective channel restrictions 145 configured to restrict bacterial cells entering the cell channels 140 from reaching the output channels 120.

[0060] In this case, step S1 may include exposing the bacterial cells captured in the cell channels 140 of the first group or groups 130 to a first antimicrobial agent or mixture and step S2 includes exposing the bacterial cells captured in the cell channels 140 of the second group or groups 130 to a second antimicrobial agent or mixture and / or exposing the bacterial cells captured in the cell channels 140 of the fourth group or groups 130 to a salt or salt mixture. The bacterial cells captured and thus present in the cell channels 140 of the first group or groups 130 are exposed to the first antimicrobial agent or mixture, preferably at the same time as the bacterial cells captured and thus present in the cell channels 140 of the second group or groups 130 are exposed to the second antimicrobial agent or mixture and / or the bacterial cells captured in the cell channels 140 of the fourth group or groups 130 are exposed to the salt or salt mixture.

[0061] A single respective antimicrobial agent may be used in steps S1 and S2. Alternatively, a mixture of two or more different antimicrobial agents may be used in any one or more of the two steps S1 and S2.

[0062] Figure 3 To illustrate Figure 2 Flow chart of the sub-routes of classification step S5 in FIG. Figure 2 The next step S10 comprises determining the Gram classification of the bacterial cells based on at least the phenotypic characteristic response of the bacterial cells to the antimicrobial agent or mixture, at least one morphological characteristic of the bacterial cells in the biological sample, or the phenotypic characteristic response of the bacterial cells to the salt or salt mixture. Thus, in this embodiment, the Gram classification of the bacterial cells is determined based on at least one of the phenotypic characteristic response of the bacterial cells to the antimicrobial agent or mixture, the morphological characteristic of the bacterial cells in the biological sample, and / or the phenotypic characteristic response of the bacterial cells to the salt or salt mixture. Figure 4 Further description.

[0063] The phenotypic characteristic response of the bacterial cell to the antimicrobial agent or mixture as used in step S10 may be the phenotypic characteristic response of the bacterial cell to the first antimicrobial agent or mixture to which the bacterial cell was exposed in step S1 or indeed other antimicrobial agents or mixtures, such as in Figure 2 In steps S2 and S3, the bacterial cells may be exposed to the second antimicrobial agent or the third antimicrobial agent, respectively. In a preferred embodiment, step S10 comprises determining the Gram classification of the bacterial cells based at least on the phenotypic characteristic response of the bacterial cells to the first antimicrobial agent or mixture, at least one morphological characteristic of the bacterial cells in the biological sample, or the phenotypic characteristic response of the bacterial cells to the salt or salt mixture.

[0064] In one embodiment, the method further comprises an optional step S11. This step S11 comprises determining the genus classification of the bacterial cells based on the phenotypic characteristic response of the bacterial cells to the second antimicrobial agent or mixture and / or the phenotypic characteristic response of the bacterial cells to the salt or salt mixture, and preferably also determining the genus classification of the bacterial cells based on the phenotypic characteristic response of the bacterial cells to the first antimicrobial agent or mixture.

[0065] These steps S10 and S11 may be performed consecutively in any order or at least partially in parallel.

[0066] This embodiment then also includes classifying the bacterial cells in step S12 based on the Gram classification determined in step S10 and the optional genus classification determined in step S11.

[0067] Thus, in this embodiment, the (first) antimicrobial agent or mixture, at least one morphological characteristic and / or a salt or salt mixture is used to determine the Gram classification of a bacterial cell, ie to determine whether a bacterial cell is likely to be Gram-positive or Gram-negative.

[0068] In bacteriology, Gram-positive bacteria are bacteria that give a positive result in a Gram stain test, which is traditionally used to quickly separate bacteria into two major groups based on their cell wall type. Gram-positive bacteria absorb the crystal violet dye used in the Gram stain test and then appear purple when viewed through a light microscope. This is because during the decolorization stage of the Gram stain test, the thick peptidoglycan layer in the bacterial cell wall retains the crystal violet dye after the crystal violet dye is washed off from the rest of the sample. In contrast, Gram-negative bacteria are unable to retain the crystal violet dye after the decolorization step. The alcohol used in this stage degrades the outer membrane of Gram-negative cells, making the cell wall more porous and unable to retain the crystal violet dye. The peptidoglycan layer of Gram-negative cells is thin and sandwiched between the inner cell membrane and the bacterial outer membrane, causing them to absorb the counterstain dye (safranine or fuchsin) and appear red or pink.

[0069] In step S10, the antimicrobial or mixture to be used is preferably the first antimicrobial, preferably an antimicrobial or mixture that has an impact on gram-positive bacteria but has no significant impact on gram-negative bacteria, or an antimicrobial or mixture that has an impact on gram-negative bacteria but has no significant impact on gram-positive bacteria. In the former case, (first) antimicrobial or mixture is a gram-positive antimicrobial that is effective to gram-positive bacteria but is invalid or at least not equivalent to gram-negative bacteria. The exemplary but non-limiting examples of gram-positive antimicrobials include glycopeptides, vancomycin and teicoplanin. In the latter case, (first) antimicrobial or mixture is a gram-negative antimicrobial that is effective to gram-negative bacteria but is invalid or at least not equivalent to gram-positive bacteria. Illustrative but non-limiting examples of Gram-negative antimicrobial agents include cephalosporins (e.g., cefepime), beta-lactamase inhibitor penicillins (e.g., piperacillin, tadalafil, ticarcillin, clavulanic acid), and carbapenems (e.g., imipenem, cilastatin, meropenem, etapenem). An illustrative example of a (first) antimicrobial agent or mixture is a combination or mixture of linezolid (LIN) and vancomycin (VAN).

[0070] The second antimicrobial agent or mixture is preferably used together with the first antimicrobial agent or mixture for determining the optional genus classification of the bacterial cells in step S11, ie determining the genus to which the bacterial cells in the biological sample belong.

[0071] Genus is a taxonomic rank used in the biological classification of organisms and viruses. In the hierarchy of biological classification, genus is located above species and below family.

[0072] Thus, the second antimicrobial agent or mixture is selected to be effective against bacteria of the first genus, but ineffective, or not equivalent, against bacteria of the second genus. Illustrative but non-limiting examples of such antimicrobials include amoxicillin and clavulanic acid (AMC) and fosfomycin (FOS), which are generally effective against Staphylococcus, but less effective against Enterococcus.

[0073] The bacterial cells are then classified in step S12 based on Gram classification and optionally based on the genus classification as determined in steps S10 and S11.

[0074] In one embodiment, Figure 3 Step S10 in comprises determining the Gram classification of the bacterial cells based on the phenotypic characteristic response of the bacterial cells to the (first) antimicrobial agent or mixture and at least one morphological characteristic of the bacterial cells in the biological sample, also referred to herein as morphological classification.

[0075] Therefore, in this embodiment, not only the phenotypic characteristic response of the bacterial cells to the (first) antimicrobial agent or mixture is used to determine the Gram classification in step S10, but also the morphology of the bacterial cells represented by at least one morphological characteristic is used to determine the Gram classification in step S10.

[0076] Morphological features used herein refer to the form, shape, size and / or structure of bacterial cells. Therefore, at least one morphological feature can represent the form or shape of bacterial cells, the size of bacterial cells or the structure of bacterial cells. As an example, at least one morphological feature can be a rod or rod-shaped (cylindrical) and a cocci or cocci (spherical). At least one morphological feature is preferably determined based on at least one image of bacterial cells. In such embodiments, at least one morphological feature can be determined based on at least one image of bacterial cells captured in the cell channel 140 of a group or multiple groups 130 of reference or control in the microfluidic chip 10. The bacterial cells captured in the reference group or multiple groups 130 are preferably not exposed to any antimicrobial agent or mixture. For example, bacterial cells captured in a reference group or groups 130 of cell channels 140 can be exposed to a culture medium, in parallel with exposure of bacterial cells captured in a first group or groups 130 of cell channels 140 to a first antimicrobial agent or mixture and exposure of bacterial cells captured in a second group or groups 130 of cell channels 140 to a second antimicrobial agent or mixture and / or exposure of bacterial cells captured in a fourth group or groups 130 of cell channels 140 to a salt or salt mixture.

[0077] Figure 4 To illustrate the embodiment according to Figure 3 Flow chart of the sub-route of step S10 in . In this embodiment, first in steps S20, S21 and S24, optional verification of data is performed. Therefore, step S20 includes determining whether valid data of at least one morphological characteristic of the bacterial cells in the biological sample are available. If such valid data are available, the method continues to step S21. Step S21 includes determining whether valid data of the phenotypic characteristic reaction (PCR) of the bacterial cells to the (first) antimicrobial agent or mixture are available. If the valid data in step S20 is not available, the method continues to step S24. This step S24 is implemented in the same manner as step S21. In another embodiment of the sub-route, first a preliminary check is performed to determine whether valid data of the phenotypic characteristic reaction of the bacterial cells to the (first) antimicrobial agent or mixture are available, and then a subsequent check is performed to determine whether valid data of at least one morphological characteristic of the bacterial cells in the biological sample are available. In such embodiments, the order of step S20 and steps S21 and S24 is thus changed.

[0078] Figure 4In the subroutines shown in , the determination of Gram classification is performed according to which valid data in any of steps S22, S23, S25 and S26 is available. In more detail, if valid data of at least one morphological characteristic of the bacterial cells and valid data of the phenotypic characteristic response of the bacterial cells to the (first) antimicrobial agent or mixture are available, the determination of Gram classification is performed as shown in step S22. Step S22 includes determining the Gram classification of the bacterial cells based on at least the phenotypic characteristic response of the bacterial cells to the (first) antimicrobial agent or mixture and at least one morphological characteristic of the bacterial cells in the biological sample.

[0079] However, if valid data for at least one morphological characteristic of the bacterial cells are available, but valid data for the phenotypic characteristic of the response of the bacterial cells to the (first) antimicrobial agent or mixture are not available, the determination of the Gram classification will be performed according to step S23. This step S23 includes determining the Gram classification of the bacterial cells based at least on the at least one morphological characteristic of the bacterial cells in the biological sample.

[0080] If valid data of the phenotypic characteristic response of the bacterial cell to the (first) antimicrobial agent or mixture is available, but valid data of at least one morphological characteristic of the bacterial cell is not available, the determination of the Gram classification is performed according to step S25. Step S25 comprises determining the Gram classification of the bacterial cell based at least on the phenotypic characteristic response of the bacterial cell to the (first) antimicrobial agent or mixture.

[0081] If no valid data is available as determined in steps S20 and S24, then no Gram classification may be inferred as in step S26.

[0082] Phenotypic characteristic reaction or at least one morphological characteristic no valid data can be attributed to various reasons.For example, there may be bubbles or non-cellular materials in the cell channel 140 of the microfluidic chip 10.Such bubbles or non-cellular materials can interfere with the morphological characteristics of the bacterial cells and / or the phenotypic characteristic reactions of the bacterial cells to (first) antimicrobial agents or mixtures.Another reason for no valid data may be that the bacterial cells captured in the cell channel 140 of the control group or groups 130 or the first group or groups 130 of the microfluidic chip 10 are too few.Another reason may be that at least one morphological characteristic of the bacterial cells or the phenotypic characteristic reactions of the bacterial cells to the first antimicrobial agents or mixtures are noisy due to other reasons.

[0083] In certain embodiments, Figure 2 Step S2 in comprises exposing the bacterial cells in the biological sample to a salt or a salt mixture, and preferably also exposing the bacterial cells in the biological sample to a second antimicrobial agent or mixture.

[0084] In this embodiment, steps S1 and S2 can be performed in any order, but are preferably performed at least partially in parallel. In this latter preferred case, bacterial cells in the biological sample are exposed to a first antimicrobial agent or mixture, and other bacterial cells in the biological sample are exposed to a second antimicrobial agent or mixture in parallel, and other bacterial cells in the biological sample are exposed to a salt or salt mixture.

[0085] In this embodiment, Figure 3 Step S10 in comprises: if no valid data is available for at least one morphological characteristic of the bacterial cells and no valid data is available for the phenotypic characteristic response of the bacterial cells to the (first) antimicrobial agent or mixture, determining the Gram classification of the bacterial cells based on the phenotypic characteristic response of the bacterial cells to salt or salt mixture.

[0086] In the embodiments described above, various methods of determining the Gram classification can be used, depending on the available valid data in the analysis. Therefore, in a preferred case, when all necessary valid data are available, the determination of the Gram classification is performed according to step S22; and if only one of the morphological characteristics and the phenotypic characteristic response of the bacterial cells to the (first) antimicrobial agent or mixture is available, the determination of the Gram classification is performed according to steps S23 or S25. If no other valid data is available when determining the Gram classification, the use of the phenotypic characteristic response of the bacterial cells to the salt or salt mixture can be considered as an alternative. Therefore, in such embodiments, Figure 4 Step S26 shown in is replaced by determining the Gram classification based at least on the phenotypic characteristic response of the bacterial cells to the salt or salt mixture.

[0087] In the above described embodiments using at least one morphological characteristic of bacterial cells, Figure 2 The method shown preferably comprises an additional step S4 which comprises determining at least one morphological feature.

[0088] In this embodiment, steps S1, S2 and S4 can be performed in any order in succession, but are preferably performed at least partially in parallel. In this latter preferred case, bacterial cells in the biological sample are exposed to a first antimicrobial agent or mixture, and other bacterial cells in the biological sample are exposed to a second antimicrobial agent or mixture and / or other bacterial cells in the biological sample are exposed to a salt or salt mixture, and at least one bacterial cell image is taken in parallel, and these bacterial cells are preferably not exposed to any antimicrobial agent or mixture or salt or salt mixture.

[0089] At least one morphological feature is preferably determined in step S4 based on at least one image of the bacterial cells in the biological sample.Step S4 is preferably performed using a neural network on an image of the cell channel 140 containing the captured bacterial cells.

[0090] In a specific embodiment, step S4 comprises monitoring the bacterial cells in the biological sample at one or preferably multiple time points while the bacterial cells are not exposed to any antimicrobial agent or mixture. In contrast, the bacterial cells are preferably exposed to a solvent, preferably a culture medium. Then, in step S4, at least one morphological characteristic is determined based on monitoring the bacterial cells at multiple time points.

[0091] In a preferred embodiment, the monitoring of bacterial cells is performed by monitoring bacterial cells in a biological sample captured in a reference group or groups 130 of cell channels 140 of a microfluidic device 5 or microfluidic chip 10. In this case, at least one morphological characteristic is determined by: for each cell channel 140 in a plurality of cell channels 140, determining at least one tentative channel-specific morphological characteristic at each time point of a plurality of time points, determining at least one channel-specific morphological characteristic of the bacterial cells captured in the cell channel 140 based on the tentative channel-specific morphological characteristic, and determining at least one morphological characteristic of the bacterial cells based on the channel-specific morphological characteristic.

[0092] In a particular embodiment, at least one tentative channel-specific morphological feature is determined by determining at least one channel-specific morphological feature based on images of bacterial cells in the cell channel 140 at each time point of multiple time points and training a computer-implemented morphological classification model for classifying bacterial cells based on the images of the bacterial cells.

[0093] In a particular embodiment, if at least a minimum percentage of the tentative channel-specific morphological features indicate a first classification, at least one channel-specific morphological feature is determined to be a first channel-specific morphological classification, such as rod or rod-shaped; if at least a minimum percentage of the tentative channel-specific morphological features indicate a second classification, at least one channel-specific morphological feature is determined to be a second channel-specific morphological feature, such as coccus or coccus-shaped, and optionally undefined otherwise. The minimum percentage is preferably a preselected value greater than 50%, such as about 75%. Then, preferably, at least one morphological feature of the bacterial cell is determined based on the quotient between the number of cell channels 140 classified as the first classification and the number of cell channels classified as the second classification.

[0094] Therefore, in one embodiment, morphological classification is based on a neural network (morphological classification model executed by a computer), which is trained to evaluate the morphological characteristics of bacterial cells based on images of a single cell channel 140 containing bacterial cells with known bacterial morphology. More specifically, the neural network has been trained based on 421 data sets, which contain 96 captured data sets of cocci and 325 rod-shaped bacteria. From these data sets, the total length of bacteria captured in all images of all cell channels 140 corresponds to 24 or higher pixels, and the growth rate is ≥0.005 / minute. This produces a total of 9727960 cell channel images, of which 676106 images contain cocci and 9051854 images contain rod-shaped bacteria. Cut the data to balance the data set, and select about 60% for training, and about 20% for respective verification and testing. When performing the splitting of training / verification / testing, all cell channel images of the same initial data set end with training / verification / testing in the same data set to ensure that these data sets are completely independent. The deep learning model is designed and trained using training data. In each epoch (i.e., iteration) of training, the deep learning model is validated against the validation data set, and the weights of the deep learning model are frozen at the epoch of the best accuracy on the validation data set. The deep learning model was tested on an independent test data set, and the binary accuracy obtained was 94.2%. During the measurement process, this neural network generates a morphological classification of each individual cell channel 140 at each time point. For each cell channel 140, the classification at each time point is summarized, and if the classification is consistent over time, the cell channel 140 is set to this morphology. If the morphology is inconsistent and switches between rod and coccus classification, it is set to "contradictory" and excluded from the final morphological score. The cell channel classification is then summarized relative to all cell channels 140 in the reference group or groups 130, and the final morphological score is calculated based on the ratio between the cell channels 140 of rods and cocci. For example, if the X cell channel 140 in the reference group or groups 130 is classified as a rod and the Y cell channel 140 in the reference group or groups 130 is classified as a coccus, the ratio can be X / (X+Y) or Y / (X+Y). If the ratio X / (X+Y) is above a defined threshold, such as 0.75, the final morphological classification in this example is a rod. Correspondingly, if the ratio Y / (X+Y) is above a defined threshold, the final morphological classification in this example is a coccus.

[0095] Figure 5 Schematically illustrates the embodiment according to Figure 3 The sub-route of step S10 in step S10 is used to determine the Gram classification of any bacterial cells present in the sample. This embodiment is particularly suitable for classifying bacterial cells present in a biological sample (such as a urine sample) taken from a subject suffering from a UTI.

[0096] In this embodiment, bacterial cells in the biological sample are exposed to a Figure 2 Four different treatments of steps S1 to S3 in the present invention are described. The first treatment includes a combination of linezolid (LIN) and vancomycin (VAN), the second treatment includes amoxicillin and clavulanic acid (AMC), the third treatment includes fosfomycin (FOS), and the fourth treatment includes a salt treatment using sodium chloride (NaCl). The LIN / VAN combination in the first treatment is generally effective against Gram-positive bacteria, but has no or little antibacterial activity against Gram-negative bacteria. Correspondingly, the salt treatment using NaCl is generally effective against Gram-negative bacteria, but has less antibacterial activity against Gram-positive bacteria, particularly little or no effect on Staphylococcus. The AMC used in the second treatment has a wide range of antibacterial activity against both Gram-positive and Gram-negative bacteria. However, it generally has a slower antibacterial activity against Staphylococcus than against Enterococcus. The FOS used in the third treatment has a wide range of antibacterial activity against both Gram-positive and Gram-negative bacteria. However, it generally has a slower antibacterial activity against Staphylococcus than against Enterococcus. The bacterial cells in the biological sample are preferably exposed to the respective treatments in parallel. In this example, after the respective treatment time, the respective influencing parameter is determined for each treatment and then compared with the respective critical value or threshold value. The respective treatment times may be the same, but are usually different and are adapted to the specific antimicrobial agent or mixture or salt or salt mixture.

[0097] In one embodiment, the impact parameter is the respective reduction in the standardized growth rate fitted to a logistic function for each antimicrobial agent or mixture (Lin / VAN, AMC, FOS) or the reduction in growth rate in the salt treatment (not the fitted data, but the average standardized growth rate over a set time interval). In one embodiment, LIN / VAN is a single treatment, but for AMC and FOS, the impact parameter is based on a "dose-response curve", i.e., a logistic curve fitted to the antibiotic effect at a set time point for all effective treatments for each antibiotic. The impact parameter is then defined as the reduction in the standardized growth rate at a defined concentration based on the fitted curve.

[0098] Gram classification first determines whether valid morphological data and valid LIN / VAN data are available, see Figure 4 If valid morphological characteristics and LIN / VAN data are available, Gram classification is determined based on linear discriminant analysis (LDA) of morphological characteristics and phenotypic characteristic responses of bacterial cells to LIN / VAN.

[0099] Valid morphological data means that at least a minimum number of cell channels 140 in a reference or control group or groups 130 in the microfluidic chip 10 have been classified as containing, for example, cocci or rods. This minimum number can represent a certain number of cell channels 140, for example, 25, and a minimum percentage of cell channels 140 in a reference or control group or groups 130 that are classified as containing, for example, cocci or rods.

[0100] Reasons why the LIN / VAN data or actual data for any other antimicrobial agent or mixture treatment may be invalid may be that the image analysis of the bacterial cells in the cell channel 140 detected bubbles, too few channels contained bacterial cells, the number of captured cells deviated too much compared to other treatments in the microfluidic chip 10 (indicating a problem with the treatment), or the growth rate data in the treatment was too noisy and the logistic curve could not be fit to the data points without large errors.

[0101] LDA, also known as normal discriminant analysis (NDA) or discriminant function analysis, is a method for finding linear combinations of features that characterize or separate two or more classes of targets or events. The resulting combination is used as a linear classifier for classifying bacterial cells as Gram-positive or Gram-negative.

[0102] In the case where no valid LIN / VAN data is available but valid morphological data is available, Gram classification is performed based on the morphological features of the bacterial cells, classifying the bacterial cells as Gram-positive or Gram-negative. For example, if the morphological features determined for the bacterial cells are rods or rod-shaped, the Gram classification is Gram-negative. Accordingly, if the morphological features determined for the bacterial cells are cocci or cocci-shaped, the Gram classification is Gram-positive.

[0103] Accordingly, if no valid morphological data are available, but valid LIN / VAN data are available, the classification of bacterial cells as Gram-positive or Gram-negative is performed based on the influence parameters determined for the LIN / VAN combination. Thus, if the bacterial cells are determined to be sensitive to LIN / VAN, they are classified as Gram-positive, and if the bacterial cells are determined to be resistant to LIN / VAN, the bacterial cells are classified as Gram-negative.

[0104] If no valid morphology or LIN / VAN data is available, Figure 2 The salt treatment performed in step S2 is used as a backup or auxiliary classification. In this case, the bacterial cells are classified as Gram-negative if they are sensitive to the salt treatment, and Gram-positive if they are resistant to the salt treatment. In the case where no valid salt treatment data are available, Gram classification cannot be performed (not applicable (N / A)).

[0105] In another embodiment, Figure 3 Step S10 in preferably comprises determining the Gram classification of the bacterial cells based on the phenotypic characteristic response of the bacterial cells to the first antimicrobial agent or mixture and the phenotypic characteristic response of the bacterial cells to the salt or salt mixture.

[0106] Thus, in this particular embodiment, the phenotypic characteristic response of the bacterial cell to the first antimicrobial agent or mixture and the salt or salt mixture is used to determine the Gram classification in step S10, e.g., to determine whether the bacterial cell is Gram-positive or Gram-negative.

[0107] Figure 7 To illustrate the embodiment according to Figure 3 Flowchart of the sub-circuit of step S10 in . The next step S30 includes determining a first candidate Gram classification of the bacterial cell based on the phenotypic characteristic response of the bacterial cell to the first antimicrobial agent or mixture. Accordingly, step S31 includes determining a second candidate Gram classification of the bacterial cell based on the phenotypic characteristic response of the bacterial cell to the salt or salt mixture.

[0108] Steps S30 and S31 may be performed consecutively in any order, or at least partially in parallel.

[0109] In one embodiment, the following step S32 includes, if the first candidate Gram classification and the second candidate Gram classification indicate the same Gram classification, determining the Gram classification of the bacterial cell to be the Gram classification indicated by the first candidate Gram classification and the second candidate Gram classification.

[0110] Therefore, this embodiment determines the candidate Gram classification of bacterial cells respectively based on the phenotypic characteristic reaction of bacterial cells to the first antimicrobial agent or mixture and salt or salt mixture.This candidate Gram classification can be regarded as the preliminary or tentative Gram classification determined based on the respective phenotypic characteristic reaction.Two candidate Gram classifications can be compared with each other, and if they indicate the same Gram classification, for example, both indicate Gram-positive or both indicate Gram-negative, the Gram classification of bacterial cells is determined to be the Gram classification indicated by both candidate Gram classifications.

[0111] In another embodiment, if the first candidate Gram classification and the second candidate Gram classification indicate different Gram classifications, then Figure 7 Step S32 in preferably comprises determining the Gram classification of the bacterial cell as a predefined Gram classification.

[0112] In this embodiment, the two candidate Gram classifications indicate different Gram classifications, i.e. one indicates Gram-positive and the other indicates Gram-negative, or one or both candidate Gram classifications indicate undefinable Gram classifications. In this case, the bacterial cell will be assigned to a predefined Gram classification in step S32.

[0113] In one embodiment, the predefined Gram classification is Gram-positive. In another preferred embodiment, the predefined Gram classification is Gram-negative.

[0114] Therefore, in a preferred embodiment, if the first and second candidate Gram classifications both indicate the same Gram classification (Gram-positive or Gram-negative), the Gram classification of the bacterial cell is determined to be the same as the Gram classification indicated by the first and second candidate Gram classifications; otherwise, it is determined to be a predefined Gram classification, preferably Gram-negative.

[0115] In one embodiment, if Figure 2 The method shown includes an additional step S3. This step S3 includes exposing the bacterial cells in the biological sample to a third antimicrobial agent or mixture. The method then continues to step S5, or any optional step S4.

[0116] In this embodiment, steps S1, S2 and S3 can be implemented in any order in succession, but are preferably implemented at least partially in parallel. In this latter preferred case, the bacterial cells in the biological sample are exposed to a first antimicrobial agent or mixture, and other bacterial cells in the biological sample are exposed to a second antimicrobial agent or mixture in parallel and / or other bacterial cells in the biological sample are exposed to a salt or salt mixture and other bacterial cells in the biological sample are exposed to a third antimicrobial agent or mixture.

[0117] In one embodiment, Figure 3 Optional step S11 in preferably includes determining the genus classification of the bacterial cells based on the phenotypic characteristic response of the bacterial cells to the second antimicrobial agent or mixture and the phenotypic characteristic response of the bacterial cells to the third antimicrobial agent or mixture, preferably determining the genus classification of the bacterial cells based on the phenotypic characteristic response of the bacterial cells to the first antimicrobial agent or mixture.

[0118] Therefore, in this particular embodiment, the phenotypic characteristic response of the bacterial cell to the second and third antimicrobial agents or mixtures, and preferably also to the first antimicrobial agent or mixture, is used to determine the genus classification in step S11, for example, to determine whether the bacterial cell is of the first genus or the second genus.

[0119] In another embodiment, step S11 includes: if valid data of the phenotypic characteristic response of the bacterial cell to the first, second and third antimicrobial agents or mixtures are available, then the genus classification of the bacterial cell is determined based on the phenotypic characteristic response of the bacterial cell to the first antimicrobial agent or mixture, the phenotypic characteristic response of the bacterial cell to the second antimicrobial agent or mixture, and the phenotypic characteristic response of the bacterial cell to the third antimicrobial agent or mixture. This embodiment also includes: if valid data of the phenotypic characteristic response of the bacterial cell to only one of the first, second and third antimicrobial agents or mixtures are available, then the genus classification in step S11 of the bacterial cell is determined based on the phenotypic characteristic response of the bacterial cell to salt or salt mixtures and the phenotypic characteristic response of the bacterial cell to one of the first, second or third antimicrobial agents or mixtures.

[0120] Figure 8 To illustrate the embodiment according to Figure 3 Flow chart of the sub-circuit of step S11 in FIG. Figure 3 The next step S40 includes determining the first candidate genus classification of the bacterial cell based on the phenotypic characteristic response of the bacterial cell to the second antimicrobial agent or the mixture. Accordingly, step S41 includes determining the second candidate genus classification of the bacterial cell based on the phenotypic characteristic response of the bacterial cell to the third antimicrobial agent or the mixture.

[0121] These steps S40 and S41 may be performed consecutively in any order, or at least partially in parallel.

[0122] In one embodiment, the next step S42 includes: if the first candidate genus classification and the second candidate genus classification indicate the same genus classification, determining the genus classification of the bacterial cell as the genus classification indicated by the first candidate genus classification and the second candidate genus classification.

[0123] Therefore, this embodiment determines the candidate genus classification of bacterial cells respectively based on the phenotypic characteristic reaction of bacterial cells to the second and third antimicrobial agents or mixtures. This candidate Gram classification can be regarded as a preliminary or tentative genus classification determined based on the respective phenotypic characteristic reaction. Then two candidate genus classifications can be compared with each other, and if they indicate the same genus classification, i.e., all indicate the same genus, the genus classification of the bacterial cell is determined to be the genus classification indicated by both candidate genus classifications.

[0124] In another embodiment, if the first candidate genus classification and the second candidate genus classification indicate different genus classifications, the genus classification is determined using a phenotypic characteristic response of the bacterial cell to the salt or salt mixture.

[0125] Thus, in this embodiment, the method comprises Figure 2Step S2 of exposing the bacterial cells to a salt or salt mixture and step S3. If the first candidate genus classification and the second candidate genus classification indicate different genus classifications, then Figure 8 Step S42 in includes determining the genus classification of the bacterial cells based on the phenotypic characteristic response of the bacterial cells to the salt or salt mixture.

[0126] In this embodiment, the two candidate genus classifications indicate different genus classifications, i.e., one indicates one genus and the other indicates another genus, or one or both candidate genus classifications indicate undefinable genus classifications. In this case, the bacterial cells in step S42 determine the genus classification based on the phenotypic characteristic response of the bacterial cells to the salt or salt mixture.

[0127] Fig. 9 To illustrate the embodiment according to Figure 3 Flowchart of the sub-circuits of the classification step S12 in step S50. In this embodiment, if the Gram classification is the first Gram classification, the bacterial cell is classified as the first order in step S50. Accordingly, if the Gram classification is the second Gram classification and the genus classification is the first genus classification, the bacterial cell is classified as the first genus in step S51. In addition, if the Gram classification is the second Gram classification and the genus classification is the second genus classification, the bacterial cell is classified as the second genus in step S52.

[0128] This means Figure 3 Steps S10 and S11 or Figure 7 Step S32 and Figure 8 The Gram and genus classifications determined in step S42 are Fig. 9 The embodiment shown is used to determine whether a bacterial cell belongs to the first order, the first genus or the second genus.

[0129] As Figure 8 In an illustrative but non-limiting example of the embodiment shown, if the Gram classification is Gram-negative, the bacterial cell in step S50 is classified as Enterobacteriales. In this example, if the Gram classification is Gram-positive and the genus classification is Staphylococcus, the bacterial cell in step S51 is classified as Staphylococcus. In this example, step S52 includes: if the Gram classification is Gram-positive and the genus classification is Enterococcus, the bacterial cell is classified as Enterococcus.

[0130] In this particular instance, Figure 7 The candidate Gram classification determined in steps S30 and S31 is thus indicated as Gram-positive or Gram-negative, while Figure 8 The candidate genus classification determined in steps S40 and S41 is indicated as Staphylococcus or Enterococcus.

[0131] The examples presented above are particularly applicable to the detection and classification of bacterial cells in a biological sample, particularly a urine sample taken from a subject suffering from a urinary tract infection (UTI).

[0132] Figure 2 In step S1 to S3, use the first to the 3rd antimicrobial or mixture and salt or salt mixture, preferably be dissolved in a solvent, particularly in a culture medium. In this case, preferably all antimicrobial or mixture and salt or salt mixture use the same solvent, such as culture medium.

[0133] In one embodiment, the method further comprises exposing the bacterial cells in the biological sample to a solvent, such as a culture medium. In this case, Figure 2 Step S5 in the method preferably comprises classifying the bacterial cells in the biological sample based on at least (i) a phenotypic characteristic response of the bacterial cells to a first antimicrobial agent or a mixture, (iia) a phenotypic characteristic response of the bacterial cells to a second antimicrobial agent or a mixture and / or (iib) a phenotypic characteristic response of the bacterial cells to a salt or a salt mixture and (iii) a reference phenotypic characteristic response of the bacterial cells to a solvent such as a culture medium.

[0134] As an example, the normalized phenotypic characteristic response can be determined as the quotient between the phenotypic characteristic response of the bacterial cells to the first or second antimicrobial agent or mixture or salt or salt mixture and the reference characteristic response. This means that Figure 2 Step S5 includes classifying the bacterial cells in the biological sample based on (i) the standardized phenotypic characteristic response of the bacterial cells to the first antimicrobial agent or mixture and (iia) the standardized phenotypic characteristic response of the bacterial cells to the second antimicrobial agent or mixture and / or (iib) the standardized phenotypic characteristic response of the bacterial cells to the salt or salt mixture.

[0135] For example, based on the normalized phenotypic characteristic response, an impact parameter ranging from 0 to 1 can be calculated. Such an impact parameter is then calculated as 1-normalized phenotypic response, i.e. PCR 处理 represents the phenotypic characteristic response of the bacterial cells treated or exposed to the first or second antimicrobial agent or mixture, and PCR 对照 Represents a reference phenotypic characteristic response of bacterial cells exposed to a solvent, such as culture medium, lacking any antimicrobial agent or mixture.

[0136] As an example, a first influencing parameter is calculated based on the phenotypic characteristic response of the bacterial cell to the first antimicrobial agent or mixture and a reference characteristic response, and a second influencing parameter is calculated based on the phenotypic characteristic response of the bacterial cell to the second antimicrobial agent or mixture and a reference characteristic response. In such an example, the bacterial cells in step S5 can be classified based on the first and second influencing parameters.

[0137] The above-described embodiments of using reference characteristic reactions and calculating influencing parameters can also be used to determine the Gram classification of step S10, determine the genus classification of step S11, determine the first candidate Gram classification of step S30, determine the second candidate Gram classification of step S31, determine the first candidate genus classification of step S40, and / or determine the second candidate genus classification of step S41. For example, as described above, the PCR 处理 The phenotypic characteristic response of bacterial cells treated with a third antimicrobial agent or mixture and thereby exposed to a third antimicrobial agent or mixture or to a salt or salt mixture may be represented.

[0138] Preferably, the bacterial cells are exposed only to a solvent such as culture medium. Figure 2 At least one morphological feature of the bacterial cells is determined in step S4. Thus, at least one image, but typically multiple images, of the cell channel 140 containing captured bacterial cells exposed to a solvent such as a culture medium is taken. The one or more images are then input into a neural network (deep learning model) as previously described herein to output a tentative classification of the bacterial cells, preferably rod-shaped (rods) or cocci-shaped (cocci).

[0139] In one embodiment, Figure 2 Step S5 of comprises: if valid data of the phenotypic characteristic response of the bacterial cell to the second antimicrobial agent or mixture is available, then classifying the bacterial cell based at least on the phenotypic characteristic response of the bacterial cell to the first antimicrobial agent or mixture and the phenotypic characteristic response of the bacterial cell to the second antimicrobial agent or mixture. In another embodiment, Figure 2 Step S5 comprises: if no valid data is available on the phenotypic characteristic response of the bacterial cells to the second antimicrobial agent or mixture, classifying the bacterial cells based at least on the phenotypic characteristic response of the bacterial cells to the first antimicrobial agent or mixture and the phenotypic characteristic response of the bacterial cells to the salt or salt mixture.

[0140] Figure 6 An embodiment of classification is schematically illustrated. This embodiment is particularly suitable for classification of bacterial cells present in a biological sample, such as a urine sample taken from a subject suffering from a UTI.

[0141] In this embodiment, if, for example, Figure 5The Gram classification implemented classifies these bacterial cells as Gram-negative, and these bacterial cells are classified as Enterobacteriales. However, if Figure 5 Bacterial cells in the strain were replaced by those classified as Gram-positive, and the classification was based on responses to the different treatments.

[0142] In this embodiment, bacterial cells in a biological sample are exposed to four different treatments. The first treatment includes Figure 2 The second processing includes the combination of LIN and VAN in step S1. Figure 2 The third processing includes the AMC of step S2. Figure 2 The FOS of step S3, and the fourth treatment is Figure 2 The step S2 is treated with sodium chloride (NaCl) salt.

[0143] An optional validation step is to first check whether valid LIN / VAN, FOS, AMC and / or salt data for implementing genus classification are available. In particular, this validation step is to check whether valid data of at least two of LIN / VAN, FOS, AMC and salt data are available. If no such data are available, genus classification cannot be performed, and bacterial cell classification is unknown. However, if valid data for at least two treatments are available, LDA-based classification is implemented. Gram-positive classification based on LDA is implemented by first calculating the antibiotic impact (the reduction of the standardized growth rate fitted to the logistic function) of each treatment (AMC, FOS, LIN / VAN) and the growth rate reduction in the salt treatment (unfitted data, but the average standardized growth rate within a set time interval). LIN / VAN is a single treatment, but for AMC and FOS, the impact is based on a "dose-response curve", which is fitted to the logistic curve of the antibiotic impact at the set time point of all effective treatments of each antibiotic. Then the impact is defined as the reduction of the standardized growth rate at a given concentration of AMC and FOS based on the fitted curve. These impact values ​​are then used as a vector, for example in the form of [AMC impact, FOS impact, salt growth rate reduction, LIN / VAN impact]. If a variable is missing, it is removed from the vector, but the order of the remaining variables is preferably maintained. If the data set is complete, or only one of the variables AMC, FOS or LIN / VAN is missing, then salt growth rate reduction is removed from the vector, as it is usually the data with the most noise.

[0144] For example, suppose valid data from AMC, FOS, and LIN / VAN treatments are available. In this case, the vector is defined as [AMC impact, FOS impact, LIN / VAN impact]. Accordingly, suppose valid data from two of the AMC, FOS, and LIN / VAN treatments are available, such as AMC and LIN / VAN treatments, then the vector is defined as [AMC impact, LIN / VAN impact]. However, if valid data from only one of the AMC, FOS, and LIN / VAN treatments is available, then the vector also includes data from the salt treatment, such as [Salt growth rate reduction, LIN / VAN impact] for the case where valid data from LIN / VAN is available but no data from AMC or FOS is available.

[0145] Based on a large number of calibration data sets, the eigenvectors of the data covariance matrix (principal components) have been calculated to maximize the variance of the projected data. The vector is then projected down onto the eigenvector by calculating the dot product of the two vectors. The resulting scalar is then compared with a threshold to determine the classification (pID). The bacterial cells are then classified as either Staphylococcus or Enterococcus.

[0146] For example, if the vector [AMC impact, FOS impact, LIN / VAN impact] is [0.1, 0.1, 0.9] and the feature vector is [0.7, 0.7, -0.2], the resulting scalar will be the dot product of the two vectors: [0.1, 0.1, 0.9] · [0.7, 0.7, -0.2] = -0.04. If this value is below a defined threshold, such as 0.5, then in this example, the classification is Enterococcus.

[0147] Thus, in one embodiment, classifying the bacterial cell comprises classifying the bacterial cell based on at least (i) a phenotypic characteristic response of the bacterial cell to a first antimicrobial agent or mixture, and (iia) a phenotypic characteristic response of the bacterial cell to a second antimicrobial agent or mixture and / or (iib) a phenotypic characteristic response of the bacterial cell to a salt or a mixture of salts if the bacterial cell has a predefined Gram classification, preferably Gram positive.

[0148] In a specific embodiment, classification of the bacterial cell comprises classification of the bacterial cell as being of the genus Staphylococcus or Enterococcus.

[0149] In one embodiment, the method comprises Figure 2. The step S3 shown in FIG. 3 includes exposing the bacterial cells in the biological sample to a third antimicrobial agent or mixture. In such embodiments, the bacterial cell classification includes classifying the bacterial cells based on at least two of the phenotypic characteristic responses of the bacterial cells to the first antimicrobial agent or mixture, the phenotypic characteristic responses of the bacterial cells to the second antimicrobial agent or mixture, the phenotypic characteristic responses of the bacterial cells to the salt or salt mixture, and the phenotypic characteristic responses of the bacterial cells to the third antimicrobial agent or mixture.

[0150] In one embodiment, the bacterial cell classification includes: if the valid data of the phenotypic characteristic response of the bacterial cell to at least two of the first, second and third antimicrobial agents or mixtures are available, the bacterial cell is classified based on the phenotypic characteristic response of the bacterial cell to at least two of the first, second and third antimicrobial agents or mixtures. In another embodiment, the bacterial cell classification includes: if the valid data of the phenotypic characteristic response of the bacterial cell to only one of the first, second and third antimicrobial agents or mixtures are available, the bacterial cell is classified based on the phenotypic characteristic response of the bacterial cell to salt or salt mixtures and the phenotypic characteristic response of the bacterial cell to one of the first, second and third antimicrobial agents or mixtures.

[0151] Figures 10 to 13 Schematically illustrates a method according to an embodiment Figure 2 This embodiment is particularly suitable for classifying bacterial cells present in a biological sample, such as a urine sample taken from a subject suffering from a UTI.

[0152] In this embodiment, bacterial cells in a biological sample are exposed to four different treatments (Tr1 to Tr4). The first treatment Tr1 includes a combination of linezolid (LIN) and vancomycin (VAN), the second treatment Tr2 includes a salt treatment of sodium chloride (NaCl), the third treatment Tr3 includes amoxicillin and clavulanic acid (AMC), and the fourth treatment Tr4 includes fosfomycin (FOS). The LIN / VAN combination in the first treatment Tr1 is generally effective against Gram-positive bacteria, but has no or little antibacterial activity against Gram-negative bacteria. Accordingly, the salt treatment Tr2 using NaCl is generally effective against Gram-negative bacteria, but has less antibacterial activity against Gram-positive bacteria, particularly little antibacterial activity or no effect on Staphylococcus. The AMC used in the third treatment Tr3 has a wide range of antibacterial activity against both Gram-positive and Gram-negative bacteria. However, it generally has a slower antibacterial activity against Staphylococcus than against Enterococcus. The FOS used in the fourth treatment Tr4 has a wide range of antibacterial activity against both Gram-positive and Gram-negative bacteria. However, it generally has a slower antibacterial activity against Staphylococci than against Enterococci. The bacterial cells in the biological sample are preferably exposed to the respective treatments in parallel. In this example, the respective influencing parameters are determined for each treatment after the respective treatment time (T1 to T5) and then compared with the respective critical values ​​or threshold values. The respective treatment times T1 to T5 may be the same, but are usually different, and the respective treatment times are adapted to the specific antimicrobial agent or mixture or salt or salt mixture.

[0153] In more detail, the Tr1 influencing parameter is compared with a first Gram cut-off value or threshold, and if the first Gram cut-off value or threshold is exceeded, the first candidate Gram classification of the bacterial cell is set to Gram-positive, otherwise it is set to Gram-negative. Correspondingly, the Tr2 influencing parameter is compared with a second Gram cut-off value or threshold, and if the second Gram cut-off value or threshold is exceeded, the second candidate Gram classification of the bacterial cell is set to Gram-negative, otherwise it is set to Gram-positive.

[0154] The Tr3 influencing parameter is compared with the first genus critical value or threshold value. If the first genus critical value or threshold value is exceeded, the first candidate genus classification of the bacterial cell is set to the genus Enterococcus, otherwise it is set to the genus Staphylococcus. Accordingly, the Tr4 influencing parameter is compared with the second genus critical value or threshold value. If the second genus critical value or threshold value is exceeded, the second candidate genus classification of the bacterial cell is set to the genus Enterococcus, otherwise it is set to the genus Staphylococcus.

[0155] Fig.11The Gram-type classification of the classification procedure according to one embodiment is schematically illustrated. In this embodiment, if the Gram test results of the first treatment Tr1 and the second treatment Tr2 are the same, that is, both indicate Gram-positive or Gram-negative, the Gram classification of the bacterial cell is selected as the Gram test result of the two treatments. If the two Gram test results are different, the Gram classification is selected as the predefined Gram classification, in this case Gram-negative. The use of Gram-negative as a predefined Gram classification is particularly suitable for analyzing biological samples, such as urine samples taken from subjects with UTIs. The reason is that such UTIs are more often caused by Gram-negative bacteria than Gram-positive bacteria, and in the rare case where the classification of the two treatments Tr1 and Tr2 disagrees, Gram-negative is preferably selected.

[0156] Fig.12 The genus classification of the classification procedure according to one embodiment is schematically illustrated. In this embodiment, if the genus test results of the third treatment Tr3 and the fourth treatment Tr4 are the same, that is, both indicate Staphylococcus or Enterococcus, the genus classification of the bacterial cell is selected as the genus test result of these two treatments. If the test results of the third and fourth treatments T3, Tr4 are different, the genus classification based on salt (NaCl) is used instead, that is, the second treatment Tr2. Generally, Enterococcus bacteria have lower salt tolerance than Staphylococcus bacteria. Therefore, if the third and fourth treatments Tr3, Tr4 give different genus test results, the salt treatment Tr2 can be used as a confirmed treatment verification. The Tr2 influencing parameter is compared with the third genus critical value or threshold value. If the third genus critical value or threshold value is exceeded, the genus classification of the bacterial cell is set to Enterococcus, otherwise it is set to Staphylococcus.

[0157] Fig.13 The final bacterial classification according to the classification procedure of one embodiment is schematically illustrated. In this embodiment, the bacterial Fig.11 If it indicates Gram-negative, the bacterial cell is classified as Enterobacteriales. However, if the Gram-type indicates Gram-positive, then Fig.12 The bacterial cells were classified as either Staphylococcus or Enterococcus based on the determined genus classification.

[0158] In one embodiment, the method for classifying bacterial cells in a biological sample includes monitoring the bacterial cells in the biological sample at multiple time points, while the bacterial cells are not exposed to any antimicrobial agent or mixture. The method also includes exposing the bacterial cells in the biological sample to an antimicrobial agent or mixture. The method further includes determining the morphological classification of the bacterial cells based on monitoring the bacterial cells at multiple time points. The method also includes classifying the bacterial cells in the biological sample based on the morphological classification and the phenotypic characteristic responses of the bacterial cells to the antimicrobial agent or mixture.

[0159] In one embodiment, monitoring bacterial cells comprises monitoring bacterial cells in a biological sample captured in a plurality of cell channels without exposure of the bacterial cells to any antimicrobial agent or mixture. In this embodiment, determining a morphological classification comprises: for each cell channel of the plurality of channels, at each time point of a plurality of time points, determining a tentative channel-specific morphological classification of the bacterial cells captured in the cell channel, determining a channel-specific morphological classification of the bacterial cells captured in the cell channel based on the tentative channel-specific morphological classification, and determining a morphological classification of the bacterial cells based on the channel-specific morphological classification.

[0160] In one embodiment, determining a tentative channel-specific morphological classification includes determining, at each time point of a plurality of time points, a tentative channel-specific morphological classification of the bacterial cells based on images of the bacterial cells in the cell channel and a computer-implemented morphological classification model trained to classify the bacterial cells based on the images of the bacterial cells.

[0161] In one embodiment, determining the channel-specific morphological classification includes: if at least a minimum portion of the tentative channel-specific morphological classification indicates the first classification, determining the channel-specific morphological classification as a first channel-specific morphological classification; if at least a minimum portion of the tentative channel-specific morphological classification indicates the second classification, determining the channel-specific morphological classification as a second channel-specific morphological classification; otherwise undefined. In this embodiment, determining the morphological classification includes: determining the morphological classification of the bacterial cell based on a quotient between the number of cell channels classified as the first classification and the number of cell channels classified as the second classification.

[0162] In one embodiment, classifying the bacterial cells includes determining a Gram classification of the bacterial cells in the biological sample based on morphological classification and a phenotypic characteristic response of the bacterial cells to the antimicrobial agent or mixture, and determining a genus classification of the bacterial cells in the biological sample based at least in part on the Gram classification.

[0163] In one embodiment, determining the genus classification includes determining the genus classification of the bacterial cell to be a first genus if the Gram classification indicates a first Gram classification.

[0164] In one embodiment, exposing the bacterial cells comprises, for each of the plurality of cell channels of the plurality of cell channels, exposing the bacterial cells in the biological sample captured in the plurality of cell channels to the respective antimicrobial agent or mixture. In this embodiment, determining the genus classification comprises: if the Gram classification indicates a second Gram classification, determining the genus classification based on the phenotypic characteristic response of the bacterial cells to the respective antimicrobial agent or mixture.

[0165] In one embodiment, determining the genus classification comprises: for each of the respective antimicrobial agents or mixtures, determining any reduction in growth rate of the bacterial cells in response to exposure to the antimicrobial agent or mixture, and if the Gram classification indicates a second Gram classification, determining the genus classification based on the reduction in growth rate of the bacterial cells in response to exposure to the respective antimicrobial agent or mixture.

[0166] In one embodiment, determining the genus classification includes calculating the dot product of the vector of reduced growth rate of the bacterial cells and the eigenvectors of the covariance matrix of the growth rate calibration data to obtain a scalar value, and determining the genus classification based on a comparison of the scalar value to a threshold value.

[0167] In one embodiment, the method further comprises determining the effectiveness of the phenotypic characteristic response of the bacterial cell to the antimicrobial agent or mixture. In this embodiment, classifying the bacterial cell comprises: classifying the bacterial cell in the biological sample based on morphological classification rather than the phenotypic characteristic response of the bacterial cell to the antimicrobial agent or mixture if the phenotypic characteristic response of the bacterial cell to the antimicrobial agent or mixture is determined to be ineffective.

[0168] In one embodiment, the method further comprises determining the effectiveness of the morphological classification of the bacterial cells. In this embodiment, exposing the bacterial cells comprises: for each of the plurality of cell channels of the plurality of cell channels, exposing the bacterial cells in the biological sample captured in the plurality of cell channels of the group to the respective antimicrobial agent or mixture. In this embodiment, classifying the bacterial cells comprises: if it is determined that the morphological classification of the bacterial cells is invalid, classifying the bacterial cells in the biological sample based on the phenotypic characteristic response of the bacterial cells to the respective antimicrobial agent or mixture rather than the morphological classification of the bacterial cells.

[0169] In one embodiment, classifying the bacterial cells comprises determining a Gram classification of the bacterial cells based on a phenotypic characteristic response of the bacterial cells to a first antimicrobial agent of a respective antimicrobial agent or a mixture or a mixture, determining a genus classification of the bacterial cells based on a phenotypic characteristic response of the bacterial cells to a second antimicrobial agent of a respective antimicrobial agent or a mixture or a mixture, and classifying the bacterial cells based on the Gram classification and the genus classification.

[0170] In one embodiment, the method further comprises exposing the bacterial cells in the biological sample to a salt or salt mixture. In this embodiment, determining the Gram classification comprises determining the Gram classification of the bacterial cells based on the phenotypic characteristic response of the bacterial cells to the first antimicrobial agent or mixture and the phenotypic characteristic response of the bacterial cells to the salt or salt mixture.

[0171] In one embodiment, determining the Gram classification includes: determining a first candidate Gram classification of the bacterial cell based on a phenotypic characteristic response of the bacterial cell to a first antimicrobial agent or a mixture, determining a second candidate Gram classification of the bacterial cell based on a phenotypic characteristic response of the bacterial cell to a salt or a salt mixture, if the first candidate Gram classification and the second candidate Gram classification indicate the same Gram classification, determining the Gram classification of the bacterial cell to be the Gram classification indicated by the first candidate Gram classification and the second candidate Gram classification, if the first candidate Gram classification and the second candidate Gram classification indicate different Gram classifications, determining the Gram classification of the bacterial cell to be a predefined Gram classification.

[0172] In one embodiment, the method further comprises exposing the bacterial cells in the biological sample to the third antimicrobial agent or mixture of the respective antimicrobial agent or mixture. In this embodiment, determining the genus classification comprises determining the genus classification of the bacterial cells based on the phenotypic characteristic responses of the bacterial cells to the second antimicrobial agent or mixture and the phenotypic characteristic responses of the bacterial cells to the third antimicrobial agent or mixture.

[0173] In one embodiment, determining the genus classification includes determining a first candidate genus of the bacterial cell based on a phenotypic characteristic response of the bacterial cell to a second antimicrobial agent or mixture, determining a second candidate genus classification based on a phenotypic characteristic response of the bacterial cell to a third antimicrobial agent or mixture, and if the first candidate genus classification and the second candidate genus classification indicate the same genus classification, determining the genus classification of the bacterial cell to be the genus classification indicated by the first candidate genus classification and the second candidate genus classification.

[0174] In one embodiment, the method further comprises exposing the bacterial cells in the biological sample to a salt or a salt mixture. In this embodiment, determining the genus classification comprises: determining a first candidate genus of the bacterial cells based on the phenotypic characteristic response of the bacterial cells to a second antimicrobial agent or a mixture, determining a second candidate genus classification of the bacterial cells based on the phenotypic characteristic response of the bacterial cells to a third antimicrobial agent or a mixture, and if the first candidate genus classification and the second candidate genus classification indicate different genus classifications, determining the genus classification of the bacterial cells based on the phenotypic characteristic response of the bacterial cells to the salt or the salt mixture.

[0175] In one embodiment, classifying the bacterial cell comprises: if the Gram classification is a first Gram classification, the bacterial cell is classified into a first order; if the Gram classification is a second Gram classification and the genus classification is a first genus classification, the bacterial cell is classified into a first genus; if the Gram classification is a second Gram classification and the genus classification is a second genus classification, the bacterial cell is classified into a second genus.

[0176] In one embodiment, classifying the bacterial cell comprises: if the Gram classification is Gram-negative, the bacterial cell is classified as Enterobacteriales; if the Gram classification is Gram-positive and the genus classification is Staphylococcus, the bacterial cell is classified as Staphylococcus; if the Gram classification is Gram-positive and the genus classification is Enterococcus, the bacterial cell is classified as Enterococcus.

[0177] By means of the aforementioned Figure 2 The method shown (including Figures 3 to 13 The classification of bacterial cells in a biological sample determined by the embodiment thereof (shown in FIG. 1 ) can be used to determine or select the CBP of a test antimicrobial agent. Thus, the classification of bacterial cells, such as Enterobacteriales, Staphylococcus, or Enterococcus in the above examples, can be used as an input to determine or select the CBP value of one or more antimicrobial agents from a published list of CBP values, such as obtained from EUCAST or CLSI.

[0178] Bacterial cell classification can also be used as Figure 5 The disclosed bacterial cells are performed as part of an assay.

[0179] Fig.14 FIG. 1 is a flow chart illustrating a method for analyzing bacteria. The method includes step S60 of exposing bacterial cells in a biological sample to a test antimicrobial agent. The next step S61 corresponds to step S62 of Figures 2 to 13 The classification of bacterial cells described previously herein. Therefore, this step S61 comprises at least Figure 2 Steps S1, S2 and S5, but preferably also include Figure 2 Steps S3 and S4. Bacterial cells in the biological sample are exposed to Figure 2 The first antimicrobial agent or mixture of step S1 and Figure 2 The second antimicrobial agent or mixture and / or salt or salt mixture of step S2.

[0180] Steps S60, S1 and S2 can be implemented in any order in succession, but are preferably implemented at least partially in parallel. In this latter preferred case, bacterial cells in the biological sample are exposed to the test antimicrobial agent, and other bacterial cells in the biological sample are exposed to the first antimicrobial agent or mixture in parallel and other bacterial cells in the biological sample are exposed to the second antimicrobial agent or mixture and / or other bacterial cells in the biological sample are exposed to salt or salt mixture.

[0181] Figure 2 The next step S5 comprises classifying the bacterial cells based at least on (i) the phenotypic characteristic response of the bacterial cells to the first antimicrobial agent or mixture and (ii) the phenotypic characteristic response of the bacterial cells to the second antimicrobial agent or mixture and / or (iib) the phenotypic characteristic response of the bacterial cells to the salt or salt mixture.

[0182] Step S61 therefore preferably corresponds to Figure 2 Steps S1, S2 and S5, and step S61 can therefore refer to Figure 2 As hereinbefore described or referred to any or all Figures 3 to 13 As in any of the embodiments described above. Therefore, in one embodiment, Fig.14 The method shown may also include corresponding Figure 2 Step S3 of exposing the bacterial cells to a third antimicrobial agent or mixture, corresponding to Figure 2 Step S2 of exposing the bacterial cells to salt or salt mixture and / or corresponding Figure 2 Step S4 determines at least one morphological feature of the bacterial cell.

[0183] The next step S62 includes based on Figure 2 The classification results of the bacterial cells in step S5 are used to determine the CBP of the test antimicrobial used in step S60. The method also includes determining the MIC of the test antimicrobial based on the phenotypic characteristic response of the bacterial cells to the test antimicrobial. The MIC is then compared with the CBP in step S64.

[0184] In one embodiment, the method comprises Fig.15 An additional step S65 is shown. This step S65 includes determining whether the bacterial cells are susceptible to the test antimicrobial agent based on a comparison between the MIC and the CBP.

[0185] In more detail, if the MIC determined in step S63 is lower than the CBP determined or selected in step S62, the bacterial strain is classified as sensitive (S) to the test antimicrobial agent; and if the MIC is higher than the CBP, the bacterial strain is classified as resistant (R) to the test antimicrobial agent.

[0186] As previously described, in some cases, two CBP values ​​are available for the antimicrobial agent and the order / family / genus / species, a sensitive CBP value and a resistant CBP value, and thus are determined for the bacterial cell in step S62. In this case, the MIC value determined in step S63 can be compared with the sensitive and resistant CBP values ​​determined in step S62 to determine whether the bacterial cell is sensitive (S), resistant (R), or intermediate (I) phenotype to the test antimicrobial agent.

[0187] The above discussion on exposing bacterial cells in biological samples to a solvent such as culture medium and determining and using reference phenotypic characteristic responses and calculating respective effect parameters also applies to Fig.14 and 15 The analytical method in .

[0188] Fig.14 The analytical method is not limited to testing a single test antimicrobial. On the contrary, a variety of different test antimicrobials can be tested, preferably in parallel. For example, in one embodiment, step S60 includes exposing the bacterial cells in the biological sample to the first test antimicrobial and exposing the bacterial cells in the biological sample to the second test antimicrobial. In this embodiment, step S62 includes determining the first CBP of the first antimicrobial and the second CBP of the second antimicrobial. In this embodiment, step S63 includes determining the first MIC of the first test antimicrobial based on the phenotypic characteristic reaction of the bacterial cell to the first test antimicrobial and determining the second MIC concentration of the second test antimicrobial based on the phenotypic characteristic reaction of the bacterial cell to the second test antimicrobial. Then in step S64, the first MIC is compared with the first CBP and the second MIC is compared with the second CBP.

[0189] The above method can also be extended to test more than two different test antimicrobial agents.

[0190] In the above embodiments, in steps S1, S2, S3, S60, S61, the bacterial cells can be exposed to a single respective concentration of the first to third antimicrobial agents or mixtures, test antimicrobial agents or salts or salt mixtures. Alternatively, in steps S1, S2, S3, S60, S61, the bacterial cells in the biological sample can be exposed to any or all of the first to third antimicrobial agents or mixtures, test antimicrobial agents or salts or salt mixtures at multiple different concentrations.

[0191] In the former case, the phenotypic characteristic response of the bacterial cells to the first antimicrobial agent, the second antimicrobial agent or the third antimicrobial agent or the test antimicrobial agent or the salt or the salt mixture at a single concentration is available and used in steps S5, S10, S11, S22, S25, S30, S31, S40, S41, S63. In the latter case, the multiple phenotypic characteristic responses of the bacterial cells to the first antimicrobial agent, the second antimicrobial agent or the third antimicrobial agent or the test antimicrobial agent or the salt or the salt mixture at multiple concentrations are available and can be used in steps S5, S10, S11, S22, S25, S30, S31, S40, S41, S63.

[0192] As an illustrative example, Fig.16The dose response curve shown can be generated by plotting or graphing the growth rate effect of the antimicrobial agent or mixture or salt or salt mixture relative to the concentration. In one embodiment, the effect parameter in the form of growth rate effect is the normalized growth rate parameter of the bacterial cells and is expressed as 1-the average growth rate of the treated bacterial cells normalized by the average growth rate of the untreated bacterial cells, i.e. Where GRI stands for Growth Rate Impact, represents the average growth rate of the treated bacterial cells, represents the average growth rate of untreated bacterial cells, ie, the average growth rate of reference or control bacterial cells that were not exposed to a particular antimicrobial agent or mixture or salt or salt mixture or were exposed only to a solvent (eg, culture medium).

[0193] In more detail, Fig.16 Specific bacterial isolates tested in separate microfluidic devices are shown. These isolates may have different MICs (degrees of sensitivity to antibiotics) measured by the reference method and given by the line coding on the right side of the graph. Fig.16 The data in show the growth rate impact (y-axis) of each isolate as a function of the antibiotic concentration (x-axis) used in the same microfluidic device. The dashed line (y=0.5) and the intercept of each curve correspond to the impact concentration measurement, which is calibrated to predict the MIC. Therefore, the Fig.16 The effect concentration was calculated from the intercept point of the dose-response curve at the predetermined threshold value shown by the dashed line. Fig.17 It was further shown that there was a correlation between the effect concentrations and the reference MIC values ​​determined using the traditional culture-based MIC method.

[0194] In a specific embodiment, in steps S1 and S61, the bacterial cells in the biological sample are exposed to at least one concentration, preferably one concentration, of the first antimicrobial agent or mixture; in steps S2 and S61, the bacterial cells in the biological sample are exposed to at least one concentration, preferably multiple concentrations, such as 4-6 concentrations, of the second antimicrobial agent or mixture; in step S4, the bacterial cells in the biological sample are exposed to at least one concentration, preferably one concentration, of a salt or salt mixture; in step S3, the bacterial cells in the biological sample are exposed to at least one concentration, preferably multiple concentrations, such as 4-6 concentrations, of the third antimicrobial agent or mixture. Accordingly, in step S60, the bacterial cells in the biological sample are exposed to at least one concentration, preferably multiple concentrations, such as 4-6 concentrations, of the test antimicrobial agent.

[0195] In one embodiment, see Fig.21, step S60 includes exposing bacterial cells captured in a cell channel 140 of one or more test groups 130 having respective channel restrictions 145 to a test antimicrobial agent, the channel restrictions 145 being configured to restrict bacterial cells entering the cell channel 140 from leaving the cell channel 140. In this embodiment, step S61 includes exposing bacterial cells captured in a first group or groups 130 of cell channels 140 having respective channel restrictions 145 to a first antimicrobial agent or mixture, the channel restrictions 145 being configured to restrict bacterial cells entering the cell channel 140 from leaving the cell channel 140. In addition, step S62 includes exposing the bacterial cells captured in the second group or multiple groups 130 of cell channels 140 having respective channel restrictions 145 to a second antimicrobial agent or mixture, wherein the channel restrictions 145 are configured to restrict the bacterial cells entering the cell channels 140 from leaving the cell channels 140, and / or exposing the bacterial cells captured in the fourth group or multiple groups 130 of cell channels 140 having respective channel restrictions 145 to a salt or a salt mixture, wherein the channel restrictions 145 are configured to restrict the bacterial cells entering the cell channels 140 from leaving the cell channels 140.

[0196] This embodiment can also be extended to a third antimicrobial agent or mixture. In this case, Figure 2 Step S3 in the method includes exposing the bacterial cells captured in the cell channels 140 of the third group or groups 130 having respective channel restrictions 145 to a third antimicrobial agent or mixture, wherein the channel restrictions 145 are configured to restrict the bacterial cells entering the cell channels 140 from leaving the cell channels 140. In one embodiment, Figure 2 Step S4 in the method comprises exposing the bacterial cells captured in the cell channels 140 of the fifth group or groups 130 having respective channel restrictions 145 to a solvent, preferably a culture medium, wherein the channel restrictions 145 are configured to restrict the bacterial cells entering the cell channels 140 from leaving the cell channels 140, and taking at least one image of the bacterial cells captured in the cell channels 140 of the fifth group or groups 130. The solvent (preferably the culture medium) mentioned above is preferably the same solvent, preferably the culture medium, in which the first to third antimicrobial agents or mixtures and the salt or salt mixture are dissolved or dispersed.

[0197] Different groups of cell channels 140 form compartments in the microfluidic chip 10 .

[0198] Therefore, the different groups 130 of cell channels 140 are preferably present in Figures 18A to 18C In the microfluidic chip 10 shown. In particular Fig. 18C As shown, the microfluidic chip 10 may include a plurality of such groups 130 of cell channels 140. Fig.19 and 20As shown, the microfluidic chip 10 , which is preferably attached to a chip carrier 20 , is then inserted into the chip chamber 2 of the substrate 1 of the microfluidic device 5 .

[0199] In one embodiment, Figure 2 The method of 14 or 15 includes loading a biological sample containing bacterial cells into a cell channel 140 of a microfluidic chip 10 having a plurality of groups 130 of cell channels 140, a plurality of input channels 110, and a plurality of output channels 120. Fig.21 As more clearly shown, each input channel 110 is in fluid communication with a respective output channel 120 via a cell channel 140 of a respective group 130 of cell channels 140. The cell channels 140 include respective channel restrictions 145 that are configured to restrict bacterial cells entering the cell channels 140 from reaching the output channels 120. The respective channel restrictions 145 are preferably arranged to be connected to or near an end 144 of the cell channels 140 that is fluidly connected to the output channels 120. Thus, the channel restrictions 145 in the cell channels 140 are preferably closer to the output channels 120 than the input channels 110.

[0200] Then, an exposing step S60 comprises exposing the bacterial cells captured in the cell channels 140 of the test group or groups 130 to a test antimicrobial agent, steps S1 and S61 comprise exposing the bacterial cells captured in the cell channels 140 of the first group or groups 130 to a first antimicrobial agent or mixture, steps S2 and S62 comprise exposing the bacterial cells captured in the cell channels 140 of the second group or groups 130 to a second antimicrobial agent or mixture and exposing the bacterial cells captured in the cell channels 140 of the fourth group or groups 130 to a salt or salt mixture, step S3 comprises exposing the bacterial cells captured in the cell channels 140 of the third group or groups 130 to a third antimicrobial agent or mixture, and step S4 comprises exposing the bacterial cells captured in the cell channels 140 of the fifth group or groups 130 to a solvent, preferably a culture medium.

[0201] Microfluidic chip 10 (see Figures 18A-18C 21) includes a plurality of groups 130 of cell channels 140. The cell channels 140 have a size sufficient to allow bacterial cells contained in the biological sample to enter the cell channels 140 from the input channel 110, such as width and height or diameter. Fig.21 As shown, each group 130 of cell channels 140 includes a plurality of substantially parallel cell channels 140 interposed between and in fluid communication with the input channel 110 and the output channel 120. Thus, a first end or input end 142 of the cell channel 140 is connected to the input channel 110, and a second end or output end 144 of the cell channel 140 is connected to the output channel 120.

[0202] Loading of the biological sample containing bacterial cells includes flowing the biological sample through the input channel 110 so that the bacterial cells enter the cell channel 140. The input channel 110 preferably has dimensions, such as width and height or diameter, that are significantly larger than the diameter of the bacterial cells in the biological sample. The biological sample containing the bacterial cells will flow through the input channel 110, typically from one end of the input channel 110 to the other end of the input channel 110. The biological sample also flows through the cell channel 140 to the output channel 120 and flows out through at least one opening or output port 121 of the output channel 120. Therefore, the bacterial cells present in the biological sample will be transported through the input channel 110 and enter the cell channel 140. However, when the biological sample flows out through the second end or output end 144 and enters the output channel 120, the bacterial cells will be captured by the channel restriction 145 and thus remain in the cell channel 140. Therefore, the channel restriction 145, also referred to herein as a channel block, thereby prevents or at least restricts the bacterial cells entering the cell channel 140 from flowing through the channel restriction 145 and entering the output channel 120. Each channel restriction 145 thus defines a narrow passageway in the portion of the cell channel 140 that contains the channel restriction 145, the narrow passageway having dimensions, such as width and height or diameter, sufficient to allow the fluid or liquid portion of the biological sample and any small cell debris present in the biological sample to pass through the narrow passageway. However, any bacterial cells that enter the cell channel 140 are too large to pass through this restricted narrow passageway and are thus trapped in the cell channel 140.

[0203] The loading of the biological sample thus results in the bacterial cells present in the biological sample being captured in the plurality of groups 130 of cell channels 140. Some of the cell channels 140 in a group 130 may each contain a single bacterial cell, some of the cell channels 140 in the group may each contain a plurality of bacterial cells, i.e., at least two bacterial cells, whereas other cell channels 140 in the group 130 do not contain any bacterial cells.

[0204] During the loading process, excess bacterial cells or cells that are too large to fit in the cell channel 140 are flushed away through the port 111 at the first end of the input channel 110. The liquid portion of the biological sample exits the set 130 of cell channels 140 from the port 111 at the first end of the input channel 110 and the opening or output port 121 of the output channel 120. The size selection capability can be used to seed the cell channel 140 with bacterial cells that are separated from, for example, significantly larger blood cells.

[0205] In steps S1, S2, S3, S4, S60 and S61, once the bacterial cells are captured in the cell channel 140, either the bacterial cells can be directly exposed to the antimicrobial agent or mixture or salt or salt mixture, or the bacterial cells in the cell channel 140 are allowed to grow and multiply for a period of time before exposing the bacterial cells in the cell channel 140 to the antimicrobial agent or mixture or salt or salt mixture or solvent (such as culture medium).

[0206] In the latter case, the bacterial cells captured in the cell channel 140 are allowed to grow along the length of the cell channel 140. The cell channel 140 is preferably of a size that allows the bacterial cells to grow in a monolayer along the length of the cell channel 140. Monolayer culture simplifies the visual representation of individual bacterial cells, which will be further described below. However, the embodiments are not limited to this. Therefore, if the size of the cell channel 140 is larger than the corresponding size of the bacterial cells (cell diameter), the bacterial cells can also be optionally grown in a multilayer culture. If the cell channel 140 is substantially only one cell diameter wide, the bacterial cells in the cell channel 140 can preferably be viewed as pearls on a string (see Fig. 22 and Fig.23 ). If the cell channel 140 is wider, the bacterial cells will form a 2D or even 3D layer in the cell channel 140.

[0207] Bacterial cells that grow and slow down through the first or input end 142 of the cell channel 140 will enter the input channel 110 and thus be washed away.

[0208] The microfluidic chip 10 of the microfluidic device 5 comprises a plurality of groups 130 of cell channels 140. This allows exposure of any captured and optionally cultured bacterial cells to one or more different antimicrobial agents or mixtures at different concentrations and salts or salt mixtures. For example, a microfluidic chip 10 having 32 groups 130 of cell channels 140 can be used for 5 different antimicrobial agents or mixtures at 5 concentrations, and then the remaining 7 groups 130 of cell channels 140 are used to expose bacterial cells to one or more salts or salt mixtures at one or more different concentrations and a control such as exposing bacterial cells to culture medium alone.

[0209] In one embodiment, Fig.14 Step S60 in the method includes exposing the bacterial cells in the biological sample to a plurality of different concentrations of the test antimicrobial agent. Then, step S65 includes determining the MIC of the test antimicrobial agent based on the phenotypic characteristic responses of the bacterial cells to the plurality of different concentrations of the test antimicrobial agent.

[0210] In this embodiment, at least two test groups of cell channels 140, but preferably at least three test groups 130 of cell channels, more preferably at least four test groups 130 of cell channels or at least five test groups 130 are used to expose the captured bacterial cells to different concentrations of the test antimicrobial agent. The higher the number of cell channels 140 of the test group 130, the higher the number of different concentrations of the test antimicrobial agent that can be tested, thereby more accurately determining the MIC of the bacterial cells to the test antimicrobial agent that can be determined in step S65. In typical applications, two to eight concentrations, preferably three to seven concentrations, more preferably four to six concentrations are sufficient for the determination of MIC, and therefore, the microfluidic chip 10 includes two to eight, preferably three to seven, more preferably four to six test groups 130 of cell channels 140.

[0211] For example, assume that the microfluidic chip 10 includes five cell channels 140 of the test groups 130, and the bacterial cells captured in each of the cell channels 140 of the five test groups 130 are exposed to the respective concentrations X. 1 To X 5 of the tested antimicrobial agents, where X 1 <X 2 <X 3 <X 4 <X 5 In one example, bacterial cells are present at a concentration of X 1 To X 3 The cells in the cell channel 140 of the test group 130 are alive and growing, but at the concentration X 4 and X 5 No cell growth is detected in the cell channel 140 of the test group 130. In this example, the MIC of the antimicrobial agent for the specific bacterial cell is determined to be X in step S65. 4 .

[0212] However, the MIC determination implemented in step S65 does not necessarily need to be based on the phenotypic characteristic response of the bacterial cells to the test antimicrobial agent at multiple different concentrations. In fact, this MIC determination can be completed by preferably monitoring the phenotypic characteristic response of the bacterial cells to the test antimicrobial agent at a single concentration over time or at multiple predetermined time points.

[0213] In such an embodiment, step S60 includes exposing the bacterial cells in the bacterial sample to a culture medium containing at least one concentration (e.g., one concentration) of the test antimicrobial. In this embodiment, the method also includes exposing the bacterial cells in the biological sample to a culture medium that does not contain the test antimicrobial. In this embodiment, step S65 includes determining the MIC of the test antimicrobial based on a standardized phenotypic characteristic reaction, the standardized phenotypic characteristic reaction is based on the phenotypic characteristic reaction of the test antimicrobial exposed to at least one concentration of the bacterial cell and the reference phenotypic characteristic reaction of the bacterial cell exposed to the culture medium, preferably at multiple time points.

[0214] In a specific embodiment, the MIC is determined in step S65 by calculating the normalized treatment growth rate mean (NTGRM) or a parameter value derived from or based on the NTGRM. The NTGRM represents the average growth rate of bacterial cells exposed to the test antimicrobial agent, which is normalized by the average growth rate of bacterial cells exposed to the culture medium. An example of a parameter based on the NTGRM source is selected from the group consisting of the standard deviation mean of the NTGRM divided by the mean (SEM) of the standard error calculated by the NTGRM at the selected time point and the slope of the NTRGRM calculated at the selected time interval.

[0215] In another specific embodiment, the MIC is determined in step S65 based on a quotient between the average growth rate of the bacterial cells exposed to the test antimicrobial agent and the average growth rate of the bacterial cells exposed to the culture medium. In another specific embodiment, the MIC is determined in step S65 based on a parameter based on 1 minus the above quotient or based on a parameter equal to 1 minus the above quotient.

[0216] The MIC determination in step S65 can be performed based on the above-mentioned standardized phenotypic characteristic reactions or parameters and the antimicrobial MIC decision support information representing the relationship between the standardized phenotypic reactions or parameters and the MIC values, see Fig.17 .

[0217] This MIC decision support information can be determined by a method comprising the steps of being performed for each of a plurality of bacterial strains having respective MIC values ​​for the antimicrobial agent.

[0218] Expose bacterial cells in a culture medium containing at least one antimicrobial of concentration, and expose bacterial cells in a culture medium lacking this antimicrobial. Monitor bacterial cells at multiple time points and determine the standardized phenotypic characteristic reaction based on the monitoring of bacterial cells at multiple time points. The standardized phenotypic characteristic reaction is based on the phenotypic characteristic reaction of bacterial cells being exposed to the culture medium containing at least one antimicrobial of concentration and the phenotypic characteristic reaction of bacterial cells being exposed to the culture medium to obtain. Then, the method comprises generating antimicrobial MIC decision support information based on the standardized phenotypic characteristic reaction of multiple bacterial strains and the MIC value of multiple microbial strains.

[0219] In a specific embodiment, the antimicrobial MIC decision support information represents the relationship between the standardized phenotypic characteristic response of multiple bacterial strains and the MIC values ​​of multiple bacterial strains. For example, the antimicrobial MIC decision support information can represent the relationship of MIC=f(x), where x represents the standardized phenotypic characteristic response, and f() is a function having parameters determined based on the standardized phenotypic characteristic response of the bacterial microorganism strain and the MIC values ​​of multiple bacterial strains, see Fig.17 .

[0220] In steps S1, S2, S3, S60, S61, exposing the bacterial cells in the cell channel to the antimicrobial agent or mixture, and in step S2 exposing the bacterial cells in the cell channel to the salt or salt mixture preferably comprises flowing a culture medium containing the respective antimicrobial agent or mixture or salt or salt mixture dissolved or dispersed in the culture medium into the cell channel 140. Thus, the culture medium containing the antimicrobial agent or mixture or salt or salt mixture dissolved or dispersed at a defined concentration is preferably directed into the input channel 110 of a group 130 of cell channels 140. The culture medium containing the dissolved or dispersed antimicrobial agent or mixture or salt or salt mixture thus flows into and through the cell channel 140, and flows out to the output channel 120, and further flows out through at least one opening 121 of the output channel 120. This flow of the culture medium containing the dissolved or dispersed antimicrobial agent or mixture or salt or salt mixture is preferably carried out for a period of time to expose the bacterial cells to the antimicrobial agent or mixture or salt or salt mixture at a defined concentration while monitoring the phenotypic characteristic response of the bacterial cells to the antimicrobial agent or mixture or salt or salt mixture. Each group 130 of cell channels 140 preferably includes a respective source of culture medium containing a dissolved or dispersed antimicrobial agent, without cross talk between groups 130 of channels 140. However, if the bacterial cells in the cell channels 140 of two or more groups 130 of cell channels 140 may be exposed to the same concentration of the same antimicrobial agent or mixture or salt or salt mixture, then they may share a single common source of culture medium containing a dissolved or dispersed antimicrobial agent or mixture or salt or salt mixture.

[0221] Figures 2 to 15 At least some of the method steps in may be computer-implemented steps implemented by a processor. As an illustrative but non-limiting example, Figure 2 Step S5 in Figure 3 Steps S10-S12, Figure 4 Steps S20-S24 in Figure 7 Steps S30-S32 in Figure 8 Steps S40-S42 in Fig. 9 Steps S50-S52 in Fig.14 Steps S62-S64 and / or Fig.15 Step S65 in may be such a computer-implemented step implemented by a processor.

[0222] Figure 2 and 14 The method preferably further comprises monitoring the bacterial cells to determine a phenotypic characteristic response of the bacterial cells to the antimicrobial agent.

[0223] Various types of phenotypic characteristic responses, also referred to herein as phenotypic (characteristic) responses, can be monitored and analyzed including but not limited to growth rate, shape, size, growth rate curve form defining growth rate changes over time, length curve form defining cell length changes over time, area curve form defining cell area changes over time, color, optical density, conductivity, heat generation, surface antigen composition as observed by affinity reagents, absorbance spectrum, and combinations of at least two such phenotypic characteristics.

[0224] Growth rate is a phenotypic characteristic or feature that can be advantageously used to determine the response of bacterial cells to an antimicrobial agent or mixture or salt or salt mixture. For example, the growth rate can be determined by monitoring the number of bacterial cells in each cell channel 140, as this number will increase over time as the cells grow. Alternatively, the growth rate can be determined by monitoring the length of the portion of the cell channel 140 occupied by the bacterial cells, see Fig. 22 and Fig.23 This length will increase over time for growing cells, but will remain constant for inactive and non-growing cells. Alternatively or additionally, the growth rate may also be determined by monitoring the area or length of the segmented cells from the image of the cell channel 140.

[0225] The growth rate can generally depend on any antimicrobial or mixture or salt or salt mixture present in the culture medium and / or the concentration of the antimicrobial or mixture or salt or salt mixture over time. In some cases, bacterial cells grow exponentially, while in other cases, bacterial cells grow in a more periodic manner. Therefore, the shape or form of the growth rate curve can be used to determine the phenotypic characteristic response of bacterial cells to an antimicrobial or mixture or salt or salt mixture.

[0226] Other phenotypic characteristics that may vary for cells in the absence and presence of an antimicrobial agent or mixture or salt or salt mixture include shape, size, color, and optical density. The optical density, color, or other spectral characteristics may vary depending on the content of the bacterial cells, the shape of the bacterial cells, etc. Thus, the optical characteristics may be used to determine the response of the bacterial cells to an antimicrobial agent or mixture or salt or salt mixture.

[0227] These above-exemplified phenotypic characteristic responses are preferably optically determinable by a camera 256 or other instrument capable of taking a picture or video of the portion of the microfluidic chip 10 containing the plurality 130 of cell channels 140 (see Fig.25 Then, the microfluidic chip 10 is preferably made of an optically transparent material so as to take pictures or videos of the bacterial cells in the cell channel 140.

[0228] A typical but non-limiting example of a material for the microfluidic chip 10 is liquid silicone rubber (LSR).

[0229] The bacterial cells in the cell channel 140 can be monitored more or less continuously or at multiple time points as the culture medium with the dissolved or dispersed antimicrobial agent flows through the cell channel 140. For example, one or more video cameras can be used to monitor the phenotypic characteristic response of the bacterial cells to the antimicrobial agent or mixture or salt or salt mixture, or one or more cameras can be used to take multiple groups 130 of pictures of the cell channel 140 at selected time points.

[0230] In a particular embodiment, a microscope, such as a phase contrast microscope, connected to a camera (e.g., a charge coupled device (CCD) and complementary metal oxide semiconductor (CMOS) camera or a confocal scanning system) for fluorescence, Raman imaging, coherent anti-Stokes Raman scattering (CARS), stimulated Raman scattering (SRS), and similar chemically sensitive techniques to provide spectral changes for dead and live cells is used to take pictures of bacterial cells in cell channel 140. This includes measurements at one or several wavelengths with or without contrast enhancing additions to the growth medium, such as chemically specific probes and dyes.

[0231] Conductivity and heat generation will depend on the chemical composition and metabolic state of the bacterial cells and can therefore form the basis for determining the cellular response of the cells to the antimicrobial agent. Conductivity and / or heat generation can be measured by electrodes or sensors of an instrument arranged in or connected to the cell channel 140.

[0232] The present invention is very useful when analyzing a biological sample containing bacteria taken from a subject with the purpose of screening an antimicrobial agent to treat a bacterial infection in the subject. For example, assume that the subject is suffering from a UTI and a urine sample taken from the subject is used as the biological sample. Then in step S60, the bacterial cells in the urine sample are exposed to the antibiotic ciprofloxacin (CIP) as a test antimicrobial agent. Assume that the MIC of CIP determined in step S63 is 1 μg / mL. It is impossible to conclude from this determined MIC value itself whether CIP can effectively treat the UTI of the subject. UTI can be caused by a variety of different bacterial cells, including Escherichia coli (Gram-negative bacteria) and Enterococcus faecalis (Gram-positive bacteria). Assume that the clinical breakpoint of CIP for Gram-negative bacteria such as Escherichia coli that cause UTI is 0.25 μg / mL, while the clinical breakpoint for Gram-positive bacteria such as Enterococcus faecalis that cause UTI is 4 μg / mL. In this illustrative example, the MIC determined in step S63 is higher than the clinical breakpoint of CIP for Gram-negative bacteria causing UTI, but lower than the clinical breakpoint of CIP for Gram-positive bacteria causing UTI. This means that if a UTI is caused by, for example, Enterococcus faecalis, it can be effectively treated with CIP, but if a UTI is caused by, for example, Escherichia coli, it cannot be effectively treated with CIP.

[0233] In this instance, Fig.14 The disclosed method is capable of determining the correct CBP for a CIP based on the phenotypic characteristic responses of the bacterial cells causing the UTI to at least a first and a second antimicrobial agent or mixture. Figure 2 Steps S1 and S2). Then Figure 2 Step S5 of classifies the bacterial cells and Fig.14 Step S62 is used to determine CBP. Therefore, Fig.14 The method can be used to determine whether the bacterial cells causing the UTI are sensitive (such as Enterococcus faecalis) or insensitive (such as Escherichia coli) to CIP based on the comparison of the MIC determined in step S63 and the CBP determined in step S62.

[0234] Illustrative but non-limiting examples of antimicrobial agents that can be used according to the present invention include glycopeptides, vancomycin, teicoplanin, cephalosporins (such as cefepime), β-lactamase inhibitor penicillins (such as piperacillin, teibactam, ticarcillin, clavulanic acid) and carbapenems (such as imipenem, cilastatin, meropenem, etapenem).

[0235] Non-limiting but illustrative examples of salts that may be used in accordance with this embodiment include sodium chloride (NaCl) and potassium chloride (KCl).

[0236] Reference Fig.18A and 18BPreferably, before arranging the microfluidic chip 10 and the chip carrier 20 in the substrate 1, the microfluidic chip 10 is first attached and bonded to the chip carrier 20 (see Fig.19 In one embodiment, the microfluidic chip 10 is attached to the chip carrier 20, for example, by Fig.18B The microfluidic chip 10 is bonded to the chip carrier 20 as shown. The chip carrier 20 with the attached microfluidic chip 10 is then inserted into the matching chip chamber or well 2 in the substrate 1, as shown in FIG. Fig.19 The chip carrier 20 is preferably attached to the substrate 1 , for example by welding, preferably laser welding, so that the chip carrier 20 is attached to the substrate 1 . Fig. 20 The microfluidic device 5 is prepared for use in Figure 2 Or an embodiment of the method shown in 14. A cover 3 has been attached to the substrate 1, and the cover 3 preferably includes an opening 4 aligned with at least part of the microfluidic chip 10 containing multiple groups 130 of cell channels 140. Therefore, these cell channels 140 can be monitored and imaged through the opening 4 during the operation of the microfluidic device 5.

[0237] As one illustrative example, chip carrier 20 may be made of polystyrene, such as optically clear polystyrene.

[0238] In one embodiment, the chip carrier 20 includes two matrices or arrays of access holes 31 to 38 that provide access to the microfluidic chip 10 through channels in the chip carrier 20 (see Fig. 18C ). Each matrix preferably includes four columns of 21 to 28 of wells 31 to 38 and N rows of wells 31 to 38. The chip carrier 20 also preferably includes a central window 29 aligned with the cell channels 140 of the plurality of groups 130.

[0239] The wells 31, 32 of the first column 21, 22 closest to the central window 29 in the chip carrier 20 are preferably connected to a reservoir 244 ( Fig.21 ). A culture medium containing at least one surfactant is preferably used to wet the channels 110, 120, 140 in the microfluidic chip 10, thereby facilitating the subsequent filling step of adding the biological sample and exposing any captured bacterial cells to the antimicrobial agent or mixture and the salt or salt mixture. Each well 31, 32 of the first column 21, 23 is connected to an opening or output port 121 of a respective output channel 120 of a set 130 of cell channels 140. The wells 33, 34 of the second column 23, 24 are preferably connected to a sample reservoir 241 ( Fig.21 Each well 33, 34 of the second column 23, 24 is connected to a respective input channel 110 of a set 130 of cell channels 140. The wells 35, 36 of the third column 25, 26 are preferably connected to a waste container 243 ( Fig.21), a waste container 243 is provided to receive any excess fluid or liquid from the cell channels 140 of the plurality of groups 130. The wells 35, 36 of the third columns 25, 26 are connected to respective ports 111 of the first ends of the input channels 110 of the cell channels 140 of the plurality of groups 130. The wells 37, 38 of the outermost fourth columns 27, 28 are each connected to a respective reagent reservoir 242 ( Fig.21 ), the reagent reservoir 242 contains an antimicrobial agent or mixture or salt or salt mixture dissolved or dispersed in a culture medium at a defined concentration. Each well 37, 38 of the fourth column 27, 28 is connected to a respective input channel 110 of a group 130 of cell channels 140.

[0240] Before loading the biological sample into the microfluidic chip 10, the channels 110, 120, 140 of the microfluidic chip 10 are preferably wetted to remove any air trapped in these channels 110, 120, 140. The microfluidic chip 10 is wetted with a culture medium including at least one surfactant contained in the reservoir 244. Therefore, pressure is applied at the pressure port connected to the reservoir 244 fluid. The culture medium containing the surfactant thus flows from the reservoir 244 into the first holes 31, 32 of the chip carrier 20. In this way, the culture medium containing the surfactant enters the multiple groups 130 cell channels 140 in the microfluidic chip 10 through the opening or output port 121 of the output channel 120, flows into the input channel 110 through the cell channel 140, and then flows out from the port 111 at the first end of the input channel 130. The excess culture medium containing the surfactant then flows into the holes 35, 37 in the third column 25, 26, and further flows into the waste device 243. This initial wetting of the microfluidic chip 10 removes any air trapped in the microfluidic chip 10, i.e., air in the set 130 of cell channels 140 and in the input and output channels 110, 120. In addition, the surfactant dissolved or dispersed in the culture medium coats the surfaces of the cell channels 140 and the input and output channels 110, 120, thereby reducing the flow resistance of the biological sample and the culture medium containing the dissolved or dispersed antimicrobial agent.

[0241] Once the wetting of the microfluidic chip 10 is completed, the biological sample flows into the microfluidic chip 10 to capture any bacterial cells present in the biological sample in the cell channel 140 therein. Pressure is applied at the pressure port connected to the fluid of the sample reservoir 241. The biological sample in the sample reservoir 241 thus flows into the holes 33, 34 in the second column 23, 24 of the chip carrier 20. The biological sample further flows into the port 112 at the second end of the input channel 110 and then enters the cell channel 140. The biological sample further flows out through the second end or output end 144 of the cell channel 140, enters the output channel 120, and flows out through the opening or output port 121, and then leaves the microfluidic chip 10 and the chip carrier 20 through the holes 31, 32 in the first column 21, 22 of the chip carrier 20. The bacterial cells present in the biological sample will be trapped in the cell channel 140 by the cell restriction 145 provided therein. Excess biological sample is allowed to flow out through the port 111 at the first end of the input channel 110 and into the waste container 243 connected to the wells 35 , 36 in the third column 25 , 26 of the chip carrier 20 .

[0242] At this point, the bacterial cells present in the biological sample have been captured in the cell channel 140 of the substrate 10, and can now be exposed to the antimicrobial or mixture or salt or salt mixture dissolved or dispersed in the culture medium in the reagent reservoir 242 loaded. Therefore, pressure is applied at the pressure port connected to the reagent reservoir 242 fluid. The pressure applied causes the culture medium containing the antimicrobial or mixture or salt or salt mixture dissolved or dispersed, or the culture medium containing the reagent or salt dissolved to flow out from the reagent reservoir 242, and enter the respective holes 37, 38 in the fourth row 27, 28 of the chip carrier 20. The culture medium containing the antimicrobial or mixture or salt or salt mixture dissolved or dispersed further flows into the port 111 of the first end of the input channel 110, and flows into the cell channel 140, and then flows out into the output channel 120 and the opening 121. This flow of culture medium means that bacterial cells captured in the cell channels 140 of one set 130 of cell channels 140 are exposed to a defined concentration of an antimicrobial agent or mixture or salt or salt mixture, while bacterial cells captured in the cell channels 140 of another set 130 of cell channels 140 may be exposed to another defined concentration of the antimicrobial agent or mixture or salt or salt mixture, or to a defined concentration of another antimicrobial agent or mixture or another salt or salt mixture, or to culture medium only. As shown, by having multiple sets 130 of cell channels 140, such as 2×N or 32, a variety of different antimicrobial agents or mixtures and a variety of different concentrations of these multiple different antimicrobial agents or mixtures can be tested for a particular biological sample and still allow for internal controls in one or more sets 130 of cell channels 140. Excess culture medium of any dissolved or dispersed antimicrobial agent flows from the opening or output port 121 into the wells 31, 32 of the first column 21, 21 and then flows out into the waste container 243.

[0243] The microfluidic chip 10 preferably includes two matrices or arrays, each having N rows of holes 31 to 38 as described above. Therefore, the microfluidic chip 10 preferably includes 2×N groups 130 of cell channels 140. For example, assuming that N is 16, the microfluidic chip 10 includes 32 groups 130 of cell channels 140. In one example, the microfluidic chip 10 and the microfluidic device 5 can be used to test five different antimicrobial agents or mixtures at five different concentrations, and then use the remaining 7 groups 130 of cell channels 140 to expose bacterial cells to one or more salts or salt mixtures at one or more different concentrations and controls, such as exposing bacterial cells to culture medium only. In this exemplary example, up to five different MIC values ​​can be determined for these five different antimicrobial agents in step S65, and up to five CBPs can be determined for these five different antimicrobial agents in step S64.

[0244] The method of the present invention is preferably carried out by Fig.24 and25 In one such embodiment, the analyzer 200 is configured to receive a microfluidic device 5 (see FIG. 5 ) preloaded with a culture medium, a surfactant, and an antimicrobial agent or mixture or salt or salt mixture. Fig.21 ).like Fig.24 Schematically indicated, the biological sample is preferably added to the sample reservoir 241 of the microfluidic device 5 before the microfluidic device 5 is inserted into a container in the analyzer 200 .

[0245] Preferably, the analyzer 200 is configured to implement the method of the present invention to expose bacterial cells in a biological sample to a test antimicrobial agent in the microfluidic device 5, to expose bacterial cells in a biological sample to a first antimicrobial agent or mixture in the microfluidic device 5, to expose bacterial cells in a biological sample to (i) a second antimicrobial agent or mixture in the microfluidic device 5 and / or (ii) a salt or salt mixture in the microfluidic device 5, to classify any bacteria present in the loaded biological sample, and preferably also determine the MIC of the bacteria. The results of the operation of the analyzer 200 can then be displayed to the user on a display 210 of the analyzer 200 or a display 210 connected (wired or wirelessly) to the analyzer 200.

[0246] Fig.25 2 is a schematic block diagram of an analyzer 200 according to one embodiment. The analyzer 200 includes a processor 220 and a memory 230, which are interconnected to enable normal software execution. In this case, the memory 230 contains instructions executable by the processor 220 to enable the processor 220 to implement the method of the present invention. The analyzer 200 also includes a display 210, a microscope 250, and a pressure source 260.

[0247] The term "processor 220" should be interpreted broadly as any circuit, system or device capable of executing program code or computer program instructions to perform specific processing, determination or computing tasks. Therefore, when executing a computer program, the processor 220 is configured to perform explicit processing tasks such as those described herein. For example, the processor 220 can be implemented using any combination of one or more suitable central processing units (CPUs), multiprocessors, microcontrollers, digital signal processors (DSPs), etc. capable of executing software instructions stored in the memory 230. The processor 220 may further be provided as at least one application specific integrated circuit (ASIC) or field programmable logic array (FPGA).

[0248] The memory 230 may also include persistent storage, which may be, for example, any single or combined magnetic memory, optical memory, solid-state memory, or even remotely mounted memory.

[0249] As mentioned above, the processor 220 is configured to control the pressure source 260 to control the flow of fluid in the microfluidic device 5 (see Fig.21 ). The pressure source 260 preferably includes a pump and a motor configured to drive the pump. The processor 220 is also preferably configured to control a microscope 250 of the analyzer or a microscope 250 connected to the analyzer. The microscope 250 preferably includes a light source 252, which is configured to illuminate the plurality of groups 130 of cell channels 140 in the microfluidic device 5; and a light detector 256, which is configured to illuminate the plurality of groups 130 of cell channels 140 in the microfluidic device 5; Fig.25 , represented by camera 256. Fig.23 As shown, this camera 256 is then configured to detect light passing through or reflected from the multiple groups 130 of cell channels 140 to determine one or more images or video frames of the multiple groups 130 of cell channels 140. The analyzer 200 may include a single camera 256 of sufficient size to monitor all groups 130 of cell channels 140 in the microfluidic device 5, or multiple cameras 256 that may operate serially or at least partially in parallel to monitor the multiple groups 130 of cell channels 140. Optionally, the camera 256 is movable relative to the multiple groups 130 of cell channels 140 in the microfluidic device 5 so as to sequentially monitor different groups 130 of cell channels 140.

[0250] The microscope 250 may also optionally include one or more objective lenses 254 arranged in the light path between the light source 252 and the camera 256 , for example upstream and / or downstream of the microfluidic device 5 .

[0251] The operation of the microscope 250 is preferably controlled by the processor 220 of the analyzer 200 .

[0252] The processor 220 is further configured to process the image or video data from the camera 256 to determine the phenotypic response of the bacterial cells to various antimicrobial agents or mixtures and salt(s) or salt mixture(s).

[0253] Thus, one aspect of the present invention relates to an analyzer 200 comprising a pressure source 260 configured to apply pressure to a microfluidic device 5, a processor 220, and a memory 230 comprising instructions executable by the processor 220, such that the processor 220 controls the pressure source 260 to expose bacterial cells in a biological sample to a first antimicrobial agent or mixture in the microfluidic device 5 and controls the pressure source 260 to expose bacterial cells in the biological sample to (i) a second antimicrobial agent or mixture in the microfluidic device 5 and / or (ii) a salt or salt mixture in the microfluidic device 5. The processor 220 further classifies the bacterial cells in the biological sample based on at least (i) a phenotypic characteristic response of the bacterial cells to the first antimicrobial agent or mixture and (iia) a phenotypic characteristic response of the bacterial cells to the second antimicrobial agent or mixture and / or (iib) a phenotypic characteristic response of the bacterial cells to the salt or salt mixture.

[0254] In one embodiment, the processor 220 controls the pressure source 260 to apply pressure to the microfluidic device 5 including multiple groups 130 of cell channels 140 configured to capture bacterial cells, so that a first antimicrobial agent or mixture flows toward the bacterial cells captured in at least one first group 130 of the multiple groups 130 of cell channels 140, and a second antimicrobial agent or mixture flows toward the bacterial cells captured in at least one second group 130 of the multiple groups 130 of cell channels 140, and / or a salt or salt mixture flows toward the bacterial cells captured in at least one fourth group 130 of the multiple groups 130 of cell channels 140.

[0255] Another aspect of the present invention relates to an analyzer 200, which includes a pressure source 260 configured to apply pressure to a microfluidic device 5, a processor 220, and a memory 230 containing instructions executed by the processor 220, so that the processor 220 controls the pressure source 260 to expose bacterial cells in a biological sample to a test antimicrobial in the microfluidic device 5, controls the pressure source 260 to expose bacterial cells in the biological sample to a first antimicrobial or mixture in the microfluidic device 5, controls the pressure source 260 to expose bacterial cells in the biological sample to (i) a second antimicrobial or mixture in the microfluidic device 5 and / or (ii) a salt or a salt mixture in the microfluidic device 5. The processor 220 also classifies the bacterial cells in the biological sample based on at least (i) a phenotypic characteristic response of the bacterial cells to the first antimicrobial or mixture, (iia) a phenotypic characteristic response of the bacterial cells to the second antimicrobial or mixture, and / or (iib) a phenotypic characteristic response of the bacterial cells to the salt or the salt mixture. The processor 220 further determines a clinical breakpoint for the test antimicrobial based on the classification results of the bacterial cells and determines a minimum inhibitory concentration for the test antimicrobial based on the phenotypic characteristic response of the bacterial cells to the test antimicrobial. The processor 220 also compares the minimum inhibitory concentration with the clinical breakpoint.

[0256] In one embodiment, the processor 220 controls the pressure source 260 to apply pressure to the microfluidic device 5 including multiple groups 130 of cell channels 140 configured to capture bacterial cells, so that the test antimicrobial agent flows to the cell channels 140 of at least one test group 130 of the multiple groups 130 of cell channels 140, the first antimicrobial agent or the mixture flows to the bacterial cells captured in at least one first group 130 of the multiple groups 130 of cell channels 140, and the second antimicrobial agent or the mixture flows to the bacterial cells captured in at least one second group 130 of the multiple groups 130 of cell channels 140, and / or the salt or the salt mixture flows to the bacterial cells captured in at least one fourth group 130 of the multiple groups 130 of cell channels 140.

[0257] The processor 220 preferably also implements the disclosed embodiments of the present invention by executing instructions stored in the memory 230. Figures 2 to 15 Various related method steps.

[0258] In one embodiment, the analyzer 200 includes a microfluidic device 5 .

[0259] In one embodiment, the analyzer 200 includes a microfluidic device 5, a pressure source 260 configured to apply pressure to the microfluidic device 5, a camera 256, a processor 220, and a memory 230. The memory 230 includes instructions executed by the processor 220 to cause the processor 220 to:

[0260] controlling the pressure source 260 to expose the bacterial cells in the biological sample to the antimicrobial agent or mixture in the microfluidic device 5;

[0261] controlling the camera 256 to capture images of bacterial cells in the biological sample captured by the microfluidic device 5 at multiple time points while the bacterial cells are not exposed to any antimicrobial agent or mixture;

[0262] Determining morphological classification of bacterial cells based on the images; and

[0263] Classify bacterial cells in a biological sample based on morphological classification and phenotypic characteristic responses of the bacterial cells to an antimicrobial agent or mixture.

[0264] In one embodiment, the memory 230 includes instructions executable by the processor 220 to cause the processor 220 to:

[0265] controlling a pressure source 260 to expose bacterial cells in the biological sample to a test antimicrobial agent;

[0266] Determine clinical breakpoints for testing antimicrobial agents based on bacterial cell classification results;

[0267] determining a minimum inhibitory concentration of the test antimicrobial agent based on the phenotypic characteristic response of the bacterial cells to the test antimicrobial agent; and

[0268] The minimum inhibitory concentrations were compared to clinical breakpoints.

[0269] Various embodiments of the present invention are provided by the following clauses.

[0270] Clause 1: A method for classifying bacteria, the method comprising:

[0271] exposing (S1) bacterial cells in a biological sample to a first antimicrobial agent or mixture;

[0272] exposing (S2) the bacterial cells in the biological sample to (i) a second antimicrobial agent or mixture and / or (ii) a salt or a salt mixture; and

[0273] The bacterial cells in the biological sample are classified (S5) based at least on (i) the phenotypic characteristic response of the bacterial cells to the first antimicrobial agent or mixture, and (iia) the phenotypic characteristic response of the bacterial cells to the second antimicrobial agent or mixture and / or (iib) the phenotypic characteristic response of the bacterial cells to the salt or salt mixture.

[0274] Clause 2: The method according to clause 1, wherein classifying the bacterial cells (S5) comprises:

[0275] If valid data on the phenotypic characteristic response of the bacterial cell to the second antimicrobial agent or mixture is available, classifying the bacterial cell based at least on the phenotypic characteristic response of the bacterial cell to the first antimicrobial agent or mixture and the phenotypic characteristic response of the bacterial cell to the second antimicrobial agent or mixture (S5); and

[0276] If no valid data is available for the phenotypic characteristic response of the bacterial cell to the second antimicrobial agent or mixture, the bacterial cell is classified based at least on the phenotypic characteristic response of the bacterial cell to the first antimicrobial agent or mixture and the phenotypic characteristic response of the bacterial cell to the salt or salt mixture (S5).

[0277] Item 3: A method according to item 1 or 2, wherein classifying the bacterial cells (S5) comprises: if the bacterial cells have a predefined Gram classification, the predefined Gram classification is preferably Gram-positive, then classifying the bacterial cells (S12) based at least on (i) the phenotypic characteristic response of the bacterial cells to the first antimicrobial agent or mixture, and (iia) the phenotypic characteristic response of the bacterial cells to the second antimicrobial agent or mixture and / or (iib) the phenotypic characteristic response of the bacterial cells to the salt or salt mixture.

[0278] Clause 4: The method according to clause 3, wherein classifying the bacterial cells (S12) comprises classifying the bacterial cells (S51, S52) as Staphylococcus or Enterococcus.

[0279] Clause 5: The method according to clause 3 or 4, further comprising:

[0280] exposing (S3) the bacterial cells in the biological sample to a third antimicrobial agent or mixture, wherein

[0281] Classifying the bacterial cells (S12) includes classifying the bacterial cells based on at least two of the phenotypic characteristic response of the bacterial cells to the first antimicrobial agent or mixture, the phenotypic characteristic response of the bacterial cells to the second antimicrobial agent or mixture, the phenotypic characteristic response of the bacterial cells to the salt or salt mixture, and the phenotypic characteristic response of the bacterial cells to the third antimicrobial agent or mixture (S12).

[0282] Clause 6: The method according to clause 5, wherein classifying the bacterial cells (S12) comprises:

[0283] If valid data for the phenotypic characteristic responses of the bacterial cells to at least two of the first, second and third antimicrobial agents or mixtures are available, classifying the bacterial cells based on the phenotypic characteristic responses of the bacterial cells to at least two of the first, second and third antimicrobial agents or mixtures (S12); and

[0284] If valid data for the phenotypic characteristic response of the bacterial cell to only one of the first, second and third antimicrobial agents or mixtures are available, the bacterial cell is classified based on the phenotypic characteristic response of the bacterial cell to the salt or salt mixture and the phenotypic characteristic response of the bacterial cell to one of the first, second and third antimicrobial agents or mixtures (S12).

[0285] Clause 7: A method according to any one of clauses 1 to 6, wherein classifying the bacterial cells (S5) comprises determining (S10) the Gram classification of the bacterial cells based at least on the phenotypic characteristic response of the bacterial cells to the antimicrobial agent or mixture, at least one morphological characteristic of the bacterial cells in the biological sample, or the phenotypic characteristic response of the bacterial cells to the salt or salt mixture.

[0286] Clause 8: The method of Clause 7, wherein the antimicrobial agent or mixture is a first antimicrobial agent or mixture.

[0287] Clause 9: The method according to clause 7 or 8, wherein determining (S10) the Gram classification comprises: if valid data of at least one morphological characteristic of the bacterial cell and valid data of the phenotypic characteristic response of the bacterial cell to the antimicrobial agent or mixture are available, then determining (S22) the Gram classification of the bacterial cell based at least on the phenotypic characteristic response of the bacterial cell to the antimicrobial agent or mixture and the at least one morphological characteristic of the bacterial cell in the biological sample.

[0288] Clause 10: A method according to any one of clauses 7 to 9, wherein determining (S10) the Gram classification comprises: if valid data of at least one morphological characteristic of the bacterial cell is available but no valid data of the phenotypic characteristic response of the bacterial cell to the antimicrobial agent or mixture is available, then determining (S23) the Gram classification of the bacterial cell based at least on the at least one morphological characteristic of the bacterial cell in the biological sample.

[0289] Clause 11: A method according to any one of clauses 7 to 10, wherein determining (S10) the Gram classification comprises: if valid data on the phenotypic characteristic response of the bacterial cell to the antimicrobial agent or mixture are available but no valid data on the at least one morphological characteristic of the bacterial cell are available, then determining (S25) the Gram classification of the bacterial cell based at least on the phenotypic characteristic response of the bacterial cell to the antimicrobial agent or mixture.

[0290] Clause 12: A method according to any one of clauses 7 to 11, wherein determining (S10) the Gram classification comprises: if no valid data is available for at least one of the morphological characteristics of the bacterial cell and no valid data is available for the phenotypic characteristic response of the bacterial cell to the antimicrobial agent or mixture, then determining (S10) the Gram classification of the bacterial cell based at least on the phenotypic characteristic response of the bacterial cell to the salt or salt mixture.

[0291] Clause 13: The method according to any one of clauses 7 to 12, wherein classifying the bacterial cells (S5) comprises

[0292] If the determined Gram classification is Gram-negative, the bacterial cell is classified (S50) as Enterobacteriales.

[0293] Clause 14: A method for bacterial analysis, comprising:

[0294] exposing (S60) bacterial cells in the biological sample to a test antimicrobial agent;

[0295] Classifying the bacterial cells according to any one of clauses 1 to 13 (S61);

[0296] determining (S62) a clinical breakpoint of the test antimicrobial agent based on the bacterial cell classification result;

[0297] determining (S63) a minimum inhibitory concentration of the test antimicrobial agent based on the phenotypic characteristic response of the bacterial cells to the test antimicrobial agent; and

[0298] The minimum inhibitory concentration is compared to the clinical breakpoint (S64).

[0299] Clause 15: The method of Clause 14, further comprising determining (S65) whether the bacterial cell is susceptible to the test antimicrobial agent based on a comparison between the minimum inhibitory concentration and the clinical breakpoint.

[0300] Clause 16: The method of clause 14 or 15, wherein:

[0301] Exposing (S60) the bacterial cells to the test antimicrobial agent comprises exposing (S60) the bacterial cells captured in the test group or groups (130) of cell channels (140) having respective channel restrictions (145) to the test antimicrobial agent, the channel restrictions (145) being configured to restrict bacterial cells entering the cell channels (140) from leaving the cell channels (140);

[0302] Exposing (S1) the bacterial cells to the first antimicrobial agent or mixture comprises exposing (S1) bacterial cells captured in a first set or multiple sets (130) of cell channels (140) having respective channel restrictions (145) to the first antimicrobial agent or mixture, wherein the channel restrictions (145) are configured to restrict bacterial cells entering the cell channels (140) from leaving the cell channels (140); and

[0303] Exposing (S2) the bacterial cells to the second antimicrobial agent or mixture includes exposing (S2) bacterial cells captured in a second group or multiple groups (130) of cell channels (140) having respective channel restrictions (145) to the second antimicrobial agent or mixture, wherein the channel restrictions (145) are configured to restrict bacterial cells entering the cell channels (140) from leaving the cell channels (140), and exposing (S2) the bacterial cells to the salt or salt mixture includes exposing (S2) bacterial cells captured in a third group or multiple groups (130) of cell channels (140) having respective channel restrictions (145) to the salt or salt mixture, wherein the channel restrictions (145) are configured to restrict bacterial cells entering the cell channels (140) from leaving the cell channels (140).

[0304] Item 17: The method described in Item 16, wherein the cell channels (140) of the test group or groups (130), the cell channels (140) of the first group or groups (130), the cell channels (140) of the second group or groups (130), and the cell channels (140) of the third group or groups (130) form a partition in the microfluidic chip (10).

[0305] Clause 18: The method according to any one of clauses 1 to 17, wherein the phenotypic characteristic response is selected from the group consisting of growth rate, degree of nucleoid compaction, degree of metabolic activity and degree of membrane integrity.

[0306] Clause 19: An analyzer (200), comprising:

[0307] a pressure source (260) configured to apply pressure to the microfluidic device (5),

[0308] a processor (220); and

[0309] A memory (230) comprising instructions executable by the processor (220) to cause the processor (220) to:

[0310] controlling the pressure source (260) to expose bacterial cells in the biological sample to the first antimicrobial agent or mixture in the microfluidic device (5); and

[0311] controlling the pressure source (260) to expose the bacterial cells in the biological sample to (i) a second antimicrobial agent or mixture and / or (ii) a salt or salt mixture in the microfluidic device (5); and

[0312] The bacterial cells in the biological sample are classified based on at least (i) a phenotypic characteristic response of the bacterial cells to the first antimicrobial agent or mixture, and (iia) a phenotypic characteristic response of the bacterial cells to the second antimicrobial agent or mixture and / or (iib) a phenotypic characteristic response of the bacterial cells to the salt or salt mixture.

[0313] Clause 20: An analyzer (200), comprising:

[0314] a pressure source (260) configured to apply pressure to the microfluidic device (5),

[0315] a processor (220); and

[0316] A memory (230) comprising instructions executable by the processor (220) to cause the processor (220) to:

[0317] controlling the pressure source (260) to expose bacterial cells in the biological sample to the test antimicrobial agent in the microfluidic device (5);

[0318] controlling the pressure source (260) to expose bacterial cells in the biological sample to the first antimicrobial agent or mixture in the microfluidic device (5);

[0319] controlling the pressure source (260) to expose the bacterial cells in the biological sample to (i) a second antimicrobial agent or mixture and / or (ii) a salt or salt mixture in the microfluidic device (5);

[0320] Classifying the bacterial cell based on at least (i) a phenotypic characteristic response of the bacterial cell to the first antimicrobial agent or mixture, and (iia) a phenotypic characteristic response of the bacterial cell to the second antimicrobial agent or mixture and / or (iib) a phenotypic characteristic response of the bacterial cell to the salt or salt mixture;

[0321] determining a clinical breakpoint for the tested antimicrobial agent based on the classification results of the bacterial cells;

[0322] determining a minimum inhibitory concentration of the test antimicrobial agent based on the phenotypic characteristic response of the bacterial cells to the test antimicrobial agent; and

[0323] The minimum inhibitory concentration was compared to the clinical breakpoint.

[0324] Item 21: The analyzer according to Item 19 or 20, further comprising the microfluidic device (5).

[0325] Example

[0326] Example 1

[0327] This example discusses Fig.14 Objective To investigate the feasibility of an analytical method to determine whether bacterial cells in urine samples from patients with UTIs are sensitive to ciprofloxacin (CIP).

[0328] The experiment of the current embodiment is as follows Figures 18A to 20 The microfluidic device 5 and the microfluidic chip 10 are shown. The reagent reservoir of the substrate 1 is pre-filled with a combination of linezolid (LIN) and vancomycin (VAN) with final concentrations of 4 μg / ml and 32 μg / ml, respectively, NaCl with a final concentration of 340 mM, five amoxicillin and clavulanic acid (AMC) with final concentrations ranging from 32 to 256 μg / ml, five fosfomycin (FOS) with final concentrations ranging from 32 to 256 μg / ml, five ciprofloxacin (CIP) with final concentrations ranging from 1 to 128 μg / ml, five nitrofurantoin with final concentrations ranging from 8 to 128 μg / ml, and five trimethoprim (TMP) with final concentrations ranging from 1 to 64 μg / ml.

[0329] Urine samples were loaded into the microfluidic device 5 and bacterial growth was monitored in the cell channels of the different groups 130. The following processing cycles were used to implement Figures 10 to 13 Classification procedure shown: T1 = 25 min; T2 to T3 = [10, 22] min (using the average normalized growth rate of all data points between these two time points); T4 = 20 min and T5 = 33 min.

[0330] According to Figures 10 to 13The results of the classification procedure shown classified the bacteria in the urine sample as Enterobacteriales (Tr1: LIN / VAL indicates Gram-negative, Tr2: NaCl indicates Gram-negative). AST for Enterobacteriales was used with AST clinical breakpoints as published by the European Commission and antibiotic CIP: sensitive if MIC ≤ 0.25 μg / ml, resistant if MIC > 0.5 μg / ml.

[0331] The MIC value of CIP as the test antimicrobial agent was determined by generating a dose response curve, which was plotted by the growth rate effect of different CIP concentrations (1 to 128 μg / ml), where growth rate effect = 1-average growth rate of CIP-treated bacterial cells normalized by the average growth rate of untreated bacterial cells. The impact concentration was calculated from the intercept of the dose response curve with a predetermined threshold value (0.2 in this example). This impact concentration was then mapped to the MIC value using a predefined calibration curve (see Fig.17 ), and the MIC value was 0.0625 μg / ml.

[0332] The determined CBP and MIC values ​​were compared, and since the determined MIC value was 0.0625 μg / ml, which was lower than 0.25 μg / ml, it was determined that the bacteria in the urine sample were sensitive to CIP.

[0333] Urine samples were also tested using the reference method. Urine (40 μl) was diluted 1:25, and 50 μl was streaked on agar plates and incubated (37°C, 16-24 hours) to isolate and count colonies (counts >100, indicating a clinical cutoff value >5×10 adopted by the system). 4 CFU / mL). This confirmed the presence of bacteria in the urine sample. The isolates grown on agar were confirmed as E. coli by matrix-assisted laser desorption / ionization time-of-flight mass spectrometry (MALDI-TOF MS), which is used in standard care at the Karolinska Microbiology Laboratory (J Microbiol Methods. 2017, 136: 17-20).

[0334] Clinical breakpoints were determined using the AST clinical breakpoints for Enterobacteriaceae (published by the AST European Committee). For antibiotic CIP: if MIC ≤ 0.25 μg / ml, it is sensitive; if MIC > 0.5 μg / ml, it is resistant.

[0335] The MIC value of the isolate to the antibiotic CIP was determined by performing broth microdilutions using commercially available Thermo Fisher Sensititre broth microdilution plates according to the manufacturer's instructions. The MIC value was determined to be 0.0625 μg / ml.

[0336] The MIC value of CBP was lower than that of CIP (0.0625 μg / ml < 0.25 μg / ml), indicating that the isolate was sensitive to CIP.

[0337] The process of the invention gave the same results as the reference method, but the invention was able to provide results after about 30 minutes, whereas the reference method required 2 days. Furthermore, the process of the invention was able to determine in parallel not only the MIC value of CIP, but also the MIC values ​​of AMC, FOS, TMP and nitrofurantoin. Thus, in only about 30 minutes, in addition to classifying the bacterial cells, the MIC values ​​of five different antibiotics were obtained in parallel.

[0338] Example 2

[0339] This example uses the method in the implementation scheme ( Figures 10 to 13 ) were used to compare the classification results with the reference method (urine culture and MALDI-TOFMS identification).

[0340] Reference sample 1

[0341] Using the method in the implementation scheme ( Fig.10 and 13 ) The test contained a concentration of 10 5 Reference sample of Escherichia coli ATCC8739 (Gram-negative) with CFU / ml. The bacteria in the reference sample were classified as Gram-negative bacteria within 30 minutes.

[0342] Reference sample 2

[0343] Using the method in the implementation scheme ( Fig.10 and 13 ) The test contained a concentration of 10 5 Reference sample of Staphylococcus saprophyticus CCUG-3706 (Gram-positive) at 100 CFU / ml. The bacteria in the reference sample were classified as Gram-positive within 30 minutes and as Staphylococcus within 45 minutes.

[0344] Reference sample 3

[0345] Using the method in the implementation scheme ( Fig.10 and 13 ) The test contained a concentration of 10 5 Reference sample of Enterococcus faecalis CCUG-9997 (Gram-positive) at 100 CFU / ml. The bacteria in the reference sample were classified as Gram-positive within 30 minutes and as Enterococcus within 45 minutes.

[0346] Patient Sample 1

[0347] The patient sample was tested using the reference method (urine culture and MALDI-TOF MS identification), which showed that the patient sample contained Staphylococcus saprophyticus (Gram-positive). The patient sample was also tested using the method described in the embodiment ( Figures 10 to 13 ) test, the results were Gram-positive and Staphylococcus spp.

[0348] Patient Sample 2

[0349] The patient sample was tested using a reference method (urine culture and MALDI-TOF MS identification), which showed that the patient sample contained Escherichia coli (Gram-negative). The patient sample was also tested using the method described in the embodiment ( Figures 10 to 13 ) tested, the results were Gram-negative and Enterobacteriales.

[0350] Patient Sample 3

[0351] The patient sample was tested using a reference method (urine culture and MALDI-TOF MS identification), which showed that the patient sample contained Enterococcus faecalis (Gram-positive). The patient sample was also tested using the method described in the embodiment ( Figures 10 to 13 ) test, the results were Gram-positive and Enterococcus spp.

[0352] Example 3

[0353] like Figure 5 The illustrated embodiment of Gram classification was tested on clinical and spiked urine samples (N=676) to investigate the accuracy of Gram classification. Fig.26A It is shown that among the 676 samples, a single biological sample indicated by an arrow in the figure was misclassified according to the present invention.

[0354] In more detail, Fig.26A PC1 and PC2 in are the two vectors used in the calibration to maximize the separation of the two Gram types (Gram-positive vs. Gram-negative). Calling these two vectors principal components in this case does not really make sense, since we are only operating in two dimensions (Gram-positive vs. Gram-negative), and principal components usually refer to such vectors in three dimensions and higher. PC1 is the actual vector in the LDA part of the Gram test (see Figure 5 ), while PC2 is used for visualization purposes only. All data points are projected onto the PC1 vector and the dashed line indicates the threshold used to separate the two Gram types.

[0355] like Figure 6As shown, for those biological samples classified as Gram-positive, genus classification was performed to classify them as Staphylococcus or Enterococcus. In this genus classification, LIN / VAN effect, AMC effect, FOS effect and salt effect were used. Salt effect was determined to be the most noisy so that if at least two other effect data were available, salt effect was not included in the genus classification. Fig.26B Shown are the results of classifying 130 biological specimens previously classified as Gram-positive using LIN / VAL impact, AMC impact, and FOS impact.

[0356] In more detail, Fig.26B PC1 and PC2 in are the first two principal components, the eigenvectors of the data covariance matrix, used in the calibration to maximize the variance of the projected data and simultaneously maximize the separation between the two bacterial types. In this case, PC1 (with the largest variance) is the actual vector used in the LDA part of the Gram-positive classification section (see Figure 6 The PC1 vector is projected onto the PC1 vector, and the dashed line represents the threshold used to separate the two bacterial classes.

[0357] Fig.26C Shown are the results of classifying 130 biological specimens previously classified as Gram-positive using the AMC effect and salt growth rate reduction, simulating a situation where no valid LIN / VAL and FOS data were available.

[0358] The embodiments described above should be understood as several exemplary embodiments of the present invention. It will be appreciated by those skilled in the art that various modifications, combinations and changes may be made to the embodiments without departing from the scope of the present invention. In particular, different partial solutions in different embodiments may be combined in other configurations when the technology is possible. However, the scope of the present invention is limited by the appended claims.

Claims

1. A method for bacterial classification, comprising: exposing (S1) bacterial cells in a biological sample to a first antimicrobial agent or mixture; exposing (S2) the bacterial cells in the biological sample to (i) a second antimicrobial agent or mixture and / or (ii) a salt or a salt mixture; and The bacterial cells in the biological sample are classified (S5) based at least on (i) the phenotypic characteristic response of the bacterial cells to the first antimicrobial agent or mixture, and (iia) the phenotypic characteristic response of the bacterial cells to the second antimicrobial agent or mixture and / or (iib) the phenotypic characteristic response of the bacterial cells to the salt or salt mixture.

2. The method according to claim 1, wherein classifying the bacterial cells (S5) comprises: If valid data on the phenotypic characteristic response of the bacterial cell to the second antimicrobial agent or mixture is available, classifying the bacterial cell based at least on the phenotypic characteristic response of the bacterial cell to the first antimicrobial agent or mixture and the phenotypic characteristic response of the bacterial cell to the second antimicrobial agent or mixture (S5); and If no valid data is available for the phenotypic characteristic response of the bacterial cell to the second antimicrobial agent or mixture, the bacterial cell is classified based at least on the phenotypic characteristic response of the bacterial cell to the first antimicrobial agent or mixture and the phenotypic characteristic response of the bacterial cell to the salt or salt mixture (S5).

3. The method according to claim 1 or 2, wherein classifying the bacterial cells (S5) comprises If the bacterial cell has a predefined Gram classification, the bacterial cell is classified (S12) based at least on (i) the phenotypic characteristic response of the bacterial cell to the first antimicrobial agent or mixture, and (iia) the phenotypic characteristic response of the bacterial cell to the second antimicrobial agent or mixture, and / or (iib) the phenotypic characteristic response of the bacterial cell to the salt or salt mixture. The method of claim 3 , wherein the predefined Gram classification is Gram-positive.

5. The method according to claim 3 or 4, wherein classifying the bacterial cells (S12) comprises classifying the bacterial cells (S51, S52) as Staphylococcus or Enterococcus.

6. The method according to any one of claims 3 to 5, further comprising: exposing (S3) the bacterial cells in the biological sample to a third antimicrobial agent or mixture, wherein Classifying the bacterial cells (S12) includes classifying the bacterial cells based on at least two of the phenotypic characteristic response of the bacterial cells to the first antimicrobial agent or mixture, the phenotypic characteristic response of the bacterial cells to the second antimicrobial agent or mixture, the phenotypic characteristic response of the bacterial cells to the salt or salt mixture, and the phenotypic characteristic response of the bacterial cells to the third antimicrobial agent or mixture (S12).

7. The method according to claim 6, wherein classifying the bacterial cells (S12) comprises: If valid data for the phenotypic characteristic responses of the bacterial cells to at least two of the first antimicrobial agent or mixture, the second antimicrobial agent or mixture, and the third antimicrobial agent or mixture are available, classifying the bacterial cells based on the phenotypic characteristic responses of the bacterial cells to at least two of the first antimicrobial agent or mixture, the second antimicrobial agent or mixture, and the third antimicrobial agent or mixture (S12); and If valid data for the phenotypic characteristic response of the bacterial cell to only one of the first antimicrobial agent or mixture, the second antimicrobial agent or mixture, and the third antimicrobial agent or mixture are available, the bacterial cell is classified based on the phenotypic characteristic response of the bacterial cell to the salt or salt mixture and the phenotypic characteristic response of the bacterial cell to one of the first antimicrobial agent or mixture, the second antimicrobial agent or mixture, and the third antimicrobial agent or mixture (S12).

8. The method according to any one of claims 1 to 5, wherein classifying the bacterial cells (S5) comprises determining (S10) the Gram classification of the bacterial cells based at least on the phenotypic characteristic response of the bacterial cells to the antimicrobial agent or mixture, at least one morphological characteristic of the bacterial cells in a biological sample, or the phenotypic characteristic response of the bacterial cells to the salt or salt mixture.

9. The method of claim 8, wherein the antimicrobial agent or mixture is the first antimicrobial agent or mixture.

10. The method according to claim 8 or 9, wherein determining (S10) the Gram classification comprises If valid data of at least one morphological characteristic of the bacterial cell and valid data of the phenotypic characteristic response of the bacterial cell to the antimicrobial agent or mixture are available, the Gram classification of the bacterial cell is determined (S22) based at least on the phenotypic characteristic response of the bacterial cell to the antimicrobial agent or mixture and at least one morphological characteristic of the bacterial cell in the biological sample.

11. The method according to claim 8 or 9, wherein determining (S10) the Gram classification comprises If valid data for at least one morphological characteristic of the bacterial cells are available but no valid data for the phenotypic characteristic response of the bacterial cells to the antimicrobial agent or mixture are available, then the Gram classification of the bacterial cells is determined (S23) based at least on the at least one morphological characteristic of the bacterial cells in the biological sample.

12. The method according to claim 8 or 9, wherein determining (S10) the Gram classification comprises If valid data are available for the phenotypic characteristic response of the bacterial cell to the antimicrobial agent or mixture but no valid data are available for at least one morphological characteristic of the bacterial cell, the Gram classification of the bacterial cell is determined (S25) at least based on the phenotypic characteristic response of the bacterial cell to the antimicrobial agent or mixture.

13. The method according to claim 8 or 9, wherein determining (S10) the Gram classification comprises If no valid data are available for at least one morphological characteristic of the bacterial cell and no valid data are available for the phenotypic characteristic response of the bacterial cell to the antimicrobial agent or mixture, the Gram classification of the bacterial cell is determined (S10) at least based on the phenotypic characteristic response of the bacterial cell to the salt or salt mixture.

14. The method according to claim 8 or 9, wherein classifying the bacterial cell (S5) comprises classifying (S50) the bacterial cell as Enterobacteriales if the determined Gram classification is Gram-negative.

15. A bacterial analysis method, comprising: exposing (S60) bacterial cells in the biological sample to a test antimicrobial agent; Classifying the bacterial cells according to any one of claims 1 to 15 (S61); determining (S62) a clinical breakpoint of the test antimicrobial agent based on the classification result of the bacterial cells; determining (S63) a minimum inhibitory concentration of the test antimicrobial agent based on the phenotypic characteristic response of the bacterial cells to the test antimicrobial agent; and The minimum inhibitory concentration is compared to the clinical breakpoint (S64).

16. The method according to claim 15, further comprising determining (S65) whether the bacterial cell is susceptible to the test antimicrobial agent based on a comparison between the minimum inhibitory concentration and the clinical breakpoint.

17. The method according to claim 15 or 16, wherein Exposing (S60) the bacterial cells to the test antimicrobial agent comprises exposing (S60) the bacterial cells captured in the test group or groups (130) of cell channels (140) having respective channel restrictions (145) to the test antimicrobial agent, the channel restrictions (145) being configured to restrict bacterial cells entering the cell channels (140) from leaving the cell channels (140); Exposing (S1) the bacterial cells to the first antimicrobial agent or mixture comprises exposing (S1) bacterial cells captured in a first set or multiple sets (130) of cell channels (140) having respective channel restrictions (145) to the first antimicrobial agent or mixture, wherein the channel restrictions (145) are configured to restrict bacterial cells entering the cell channels (140) from leaving the cell channels (140); and Exposing (S2) the bacterial cells to the second antimicrobial agent or mixture includes exposing (S2) bacterial cells captured in a second group or multiple groups (130) of cell channels (140) having respective channel restrictions (145) to the second antimicrobial agent or mixture, wherein the channel restrictions (145) are configured to restrict bacterial cells entering the cell channels (140) from leaving the cell channels (140), and exposing (S2) the bacterial cells to the salt or salt mixture includes exposing (S2) bacterial cells captured in a third group or multiple groups (130) of cell channels (140) having respective channel restrictions (145) to the salt or salt mixture, wherein the channel restrictions (145) are configured to restrict bacterial cells entering the cell channels (140) from leaving the cell channels (140).

18. The method according to claim 17, wherein the cell channels (140) of the test group or groups (130), the cell channels (140) of the first group or groups (130), the cell channels (140) of the second group or groups (130) and the cell channels (140) of the third group or groups (130) form a partition in the microfluidic chip (10).

19. The method of claim 1 or 15, wherein the phenotypic characteristic response is selected from the group consisting of growth rate, degree of nucleoid compaction, degree of metabolic activity, and degree of membrane integrity.

20. An analyzer (200), comprising: a pressure source (260) configured to apply pressure to the microfluidic device (5), Processor (220); and A memory (230) comprising instructions executable by the processor (220) to cause the processor (220) to: controlling the pressure source (260) to expose bacterial cells in the biological sample to the first antimicrobial agent or mixture in the microfluidic device (5); controlling the pressure source (260) to expose the bacterial cells in the biological sample to (i) a second antimicrobial agent or mixture and / or (ii) a salt or salt mixture in the microfluidic device (5); and The bacterial cells in the biological sample are classified based on at least (i) the phenotypic characteristic response of the bacterial cells to the first antimicrobial agent or mixture, and (iia) the phenotypic characteristic response of the bacterial cells to the second antimicrobial agent or mixture and / or (iib) the phenotypic characteristic response of the bacterial cells to the salt or salt mixture.

21. An analyzer (200), comprising: a pressure source (260) configured to apply pressure to the microfluidic device (5), Processor (220); and A memory (230) comprising instructions executable by the processor (220) to cause the processor (220) to: controlling the pressure source (260) to expose bacterial cells in the biological sample to the test antimicrobial agent in the microfluidic device (5); controlling the pressure source (260) to expose bacterial cells in the biological sample to the first antimicrobial agent or mixture in the microfluidic device (5); controlling the pressure source (260) to expose the bacterial cells in the biological sample to (i) a second antimicrobial agent or mixture and / or (ii) a salt or salt mixture in the microfluidic device (5); Classifying the bacterial cells based on at least (i) a phenotypic characteristic response of the bacterial cells to the first antimicrobial agent or mixture, and (iia) a phenotypic characteristic response of the bacterial cells to the second antimicrobial agent or mixture and / or (iib) a phenotypic characteristic response of the bacterial cells to the salt or salt mixture; determining a clinical breakpoint for the test antimicrobial agent based on the classification results of the bacterial cells; determining a minimum inhibitory concentration of the test antimicrobial agent based on the phenotypic characteristic response of the bacterial cells to the test antimicrobial agent; and The minimum inhibitory concentration was compared to the clinical breakpoint.

22. The analyzer according to claim 20 or 21, further comprising the microfluidic device (5).

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