WO2019139942A1 - Plate-forme de détection précoce d'une infection à pathogènes - Google Patents

Plate-forme de détection précoce d'une infection à pathogènes Download PDF

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Publication number
WO2019139942A1
WO2019139942A1 PCT/US2019/012835 US2019012835W WO2019139942A1 WO 2019139942 A1 WO2019139942 A1 WO 2019139942A1 US 2019012835 W US2019012835 W US 2019012835W WO 2019139942 A1 WO2019139942 A1 WO 2019139942A1
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Prior art keywords
interaction
change
detecting
platform
indicative
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PCT/US2019/012835
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English (en)
Inventor
Else M. Vedula
Kirsty A. MCFARLAND
Amanda Nicole BILLINGS-SIUTI
Andrew P. MAGYAR
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The Charles Stark Draper Laboratory, Inc.
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Application filed by The Charles Stark Draper Laboratory, Inc. filed Critical The Charles Stark Draper Laboratory, Inc.
Priority to US16/961,173 priority Critical patent/US20200363398A1/en
Priority to EP19705839.9A priority patent/EP3737944A1/fr
Publication of WO2019139942A1 publication Critical patent/WO2019139942A1/fr

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/5005—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells
    • G01N33/5008—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells for testing or evaluating the effect of chemical or biological compounds, e.g. drugs, cosmetics
    • G01N33/502—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells for testing or evaluating the effect of chemical or biological compounds, e.g. drugs, cosmetics for testing non-proliferative effects
    • G01N33/5038—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells for testing or evaluating the effect of chemical or biological compounds, e.g. drugs, cosmetics for testing non-proliferative effects involving detection of metabolites per se
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12M—APPARATUS FOR ENZYMOLOGY OR MICROBIOLOGY; APPARATUS FOR CULTURING MICROORGANISMS FOR PRODUCING BIOMASS, FOR GROWING CELLS OR FOR OBTAINING FERMENTATION OR METABOLIC PRODUCTS, i.e. BIOREACTORS OR FERMENTERS
    • C12M1/00—Apparatus for enzymology or microbiology
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/02—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving viable microorganisms
    • C12Q1/18—Testing for antimicrobial activity of a material
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/5005—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells
    • G01N33/5008—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells for testing or evaluating the effect of chemical or biological compounds, e.g. drugs, cosmetics
    • G01N33/5014—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells for testing or evaluating the effect of chemical or biological compounds, e.g. drugs, cosmetics for testing toxicity
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2500/00—Screening for compounds of potential therapeutic value
    • G01N2500/10—Screening for compounds of potential therapeutic value involving cells

Definitions

  • the invention relates to methods of assessing biological
  • interactions/associations between biological entities such as cells and viruses, and in particular, to methods and systems for ascertaining interaction between a virus or cell and other biological agents, such as an antibody or a biological substance such as a toxin.
  • the invention features a method for monitoring or identifying a molecular or biological interaction or association between one, or more, biological entities or units (also referred to herein as“agents”).
  • a biological“entity” or“unit” is defined herein as a cell(s) or cell(s) obtained from an organism (e.g., a mammal or human) or from an organism’s tissue or blood (e.g., kidney tissue, whole blood or serum).
  • a biological entity can also include a pathogenic entity, or a substance derived from, or produced by, a pathogenic entity.
  • a pathogenic entity can be a microbial pathogen such as a vims, bacterium, fungus or any other pathogenic microorganism,
  • an interaction can be a biological interaction between a viral pathogen and a biological agent/entity such as a cell or tissue.
  • the biological interaction can be between a pathogenic substance such as a toxic substance, or toxin, produced by a microorganism (or from a plant) and a cell.
  • Toxins can be an exotoxin or endotoxin (e.g., from Clostridium botulinum, Clostridium tetani, Bacillus anthracis, E.
  • the biological interaction between the toxin and the cell may result in cell lysis.
  • Toxins can also be chemically/synthetically produced as well as biologically or environmentally produced.
  • the interaction can be between a virus, a cell and an antibody that neutralizes the virus and inhibits cell entry resulting in the inhibition of virus replication and cell lysis.
  • Another example - is the interaction between a bacterium, human tissue, and an antibacterial drug that neutralizes bacterial virulence.
  • the interaction can be between a cell toxin, a cell and an antibody that neutralizes the toxic effect of the toxin and inhibits cell damage or lysis.
  • the method can continue to monitor the characteristics of the cell for regeneration and growth. For example, after the exposure of a cell to a toxin and candidate neutralizing antibody, and the confirmation that the antibody neutralizes the toxin, the cell can be monitored for characteristic activities or functions indicating cell survival or regeneration. Such characteristics are known to those of skill in the art.
  • Such a method includes providing a platform for supporting cell growth in high throughput (see for example, U.S. Patent No. 10,018, 620, and U.S. Application
  • Such a platform includes a plurality of interaction sites, comprised of substrates supportive of long term cell culture, controlled fluid delivery mechanisms, and the ability to monitor interaction between at least 2 biological entities.
  • the interaction sites may be microfluidic in nature and comprise a 2D cell culture substrate or an architecture to encourage 3D formation of biological entity interaction.
  • the cell culture substrate could be a semi-permeable membrane.
  • the culture environment could be a 3D gel. Real-time monitoring of biological entity interaction can be non destructive and multiplexed.
  • the method continues with the seeding of the different interaction sites with different biological agents. These biological agents include cells or cells in combination with other substances, such as antibodies.
  • the platform is equipped to deliver controlled amounts of fluid flow for nutrient and oxygen perfusion to the biological agents. Then, the method continues with the perfusion of the platform with a fluid that carries substances for promoting growth and maintenance of the cells and exposure of all of the interaction sites to a solution containing bacteria or viruses, for example.
  • activity detection means can be, for example, integrated into the apparatus/platform for real-time, or substantially real-time, monitoring, or can be a subsequently performed assay apart from the platform for the detection of chemical or biological substances such as the expression of specific proteins.
  • the detectable activity provides evidence indicative of a change in composition or structure of a medium at the interaction site.
  • suitable platforms for assessing such biological interactions can include micro-bead carriers, or other suitable materials to form scaffolds for cells, in particular adherent cells. Further, such scaffolds can be provided in droplets for microfluidic analysis.
  • the pathogens are selected to be microorganisms such as viruses, bacteria or yeast, and the medium is an intracellular medium, whereas in others, the medium is an extracellular medium.
  • seeding the different interaction sites of the platform with different biological agents comprises seeding the interaction sites with different kinds of cells, for example those in which evidence indicates virus replication.
  • seeding the different interaction sites of the platform with different biological agents comprises seeding the interaction sites with different kinds of antibodies and the same kind of cell.
  • these are practices in which the evidence indicates that an antibody prevented infection of cells.
  • seeding different interaction sites of the platform with different biological agents includes seeding the interaction sites with different kinds of antimicrobial agents and the same kind of cell.
  • Other embodiments of the present invention include those in which detecting evidence indicative of the interaction includes detecting evidence of virus replication and those in which detecting evidence includes detecting evidence indicative of antibody activity, such as antibodies preventing infection of cells.
  • Yet other embodiments include those in which detecting evidence indicative of the interaction includes detecting evidence of pathogen replication and those in which detecting evidence includes detecting evidence indicative of antimicrobial agent activity, such as antimicrobial agents preventing interaction between microbes and cells.
  • detecting evidence indicative of the interaction include detecting a change in metabolite level, those in which it includes detecting levels of an intracellular compound, those in which it includes detecting a level of an extracellular compound, those in which it includes detecting a level of a compound that is depleted during the course of pathogen formation, and those in which it includes detecting a level of a compound that is synthesized during the course of pathogen formation.
  • Some embodiments include those in which detecting evidence indicative of the interaction comprises detecting a glucose level.
  • detecting evidence indicative of the interaction comprises detecting a change in metabolite level, an example of which would be a change in ATP level.
  • detecting evidence indicative of the interaction comprises detecting a change in at least one of pH and pOH, or detecting evidence of occurrence of a redox reaction.
  • detecting evidence indicative of the interaction comprises optically detecting evidence of changes in aggregation of matter within a cell. Such changes are indicative of some kind of cellular change. In cases where a cell has been exposed to a pathogen, such a change could be evidence of pathogen formation. For example, in the case where the pathogen is a virus, such a change can be indicative of viral replication.
  • a variety of ways are available to detect such changes in aggregation. Among these are dynamic light scattering. A particularly useful method is to use angle-resolved low-coherence interferometry. This is particularly useful when observing backscatter in an optically complex environment.
  • Additional embodiments of the invention include those in which detecting evidence indicative of the interaction comprises using dynamic light scattering to detect evidence of virus formation, those in which it includes using an interferometer to detect evidence of virus formation, and those in which it includes using angle-resolved low- coherence interferometry to detect evidence of virus formation.
  • Some embodiments include the additional step of, based on the interaction, identifying a host for the virus.
  • Other embodiments include the additional step of, based on the interaction, identifying an antibody against the virus.
  • seeding the different interaction sites of the platform with different biological agents comprises seeding at least one of the interaction sites with a plurality of antibodies and the same kind of cell.
  • These examples can include the further step of identifying which of the antibodies is effective at blocking infection.
  • a suitable method for doing so includes carrying out a binary search.
  • Other examples include, after having identified the interaction, identifying a pathogen that engaged in the interaction and seeding a bioreactor with that identified pathogen.
  • Also examples are those that include, after having identified the interaction, identifying a biological agent that engaged in the interaction and producing additional amounts of said biological agent.
  • the invention features an apparatus/device comprising a platform and a fluid delivery system that is coupled to the platform for providing an environment conducive to cell growth and maintenance on the platform.
  • the platform comprises one, or more, interaction sites that are separated from each other.
  • An activity detector is used to monitor the specific interaction(s) at the one, or more sites.
  • the activity detector can be coupled to, or integrated into, the apparatus or platform.
  • the activity detector can comprise a detection means separated from the apparatus/platform, wherein the activity detector comprises means for performing one, or more, biochemical assays suitable for specifically detecting the desired interaction.
  • the detection can comprise, for example, obtaining a sample (e.g., removing a sample of supernatant from a reaction well or channel at a specific reaction site) and assaying the sample (in real-time or later) with a suitable chemical or biological assay.
  • the activity detector detects evidence of an interaction between a biological agent and a pathogen at the interaction site.
  • the evidence includes a change in either structure or composition of a medium at the interaction site, and can include, for example, transepithelial electrical resistance (TEER) or biochemical assessment of expressed or suppressed substances such as cytokines.
  • TEER transepithelial electrical resistance
  • the activity detector comprises an interferometer.
  • interferometers that provide an angular distribution of light that has been back-scattered from the interaction site. This light can then be used in connection with obtaining structural information about subsurface layers.
  • the interferometer is detector is configured to carry out angle-resolved, low- coherence interferometry.
  • Additional embodiments include those in which the activity detector provides data representative of dynamically scattered light to a processor that recovers, at least in part on the basis of the data, information indicative of a change in structure at the interaction site.
  • the activity detector detects a change in chemical composition.
  • activity detectors that detect a change in a concentration of metabolite at the interaction site, or a change, at the interaction site, of a concentration of a substance.
  • An example of such a change is a change in glucose levels at the interaction site.
  • Other embodiments include those in which the activity detector detects a change in an ion concentration at the interaction site, or evidence of a redox reaction at the interaction site, or a change in an electrical property of a medium at the interaction site.
  • FIG. 1 is a schematic view of an apparatus for identifying an interaction between a pathogen and a biological agent
  • FIG. 2 shows a method for using the apparatus shown in FIG. 1.
  • FIG. 3 depicts the experimental setup using four uropathogenic E. coli strains with the renal proximal tubule kidney tissue model, assessed in quadruplicate at MOI of 10 and 100, after lh and 8h, using a total of 64 out of the 96 available interaction sites.
  • Another 16 sites were used as negative controls, using a total of 80 interaction sites out of 96.
  • FIG. 4A-D are photomicrographs depicting the results of immunofluorescence detection at the 1 hour timepoint.
  • FIG.5 A-D are photomicrographs depicting the results of immunofluorescence detection at the 8 hour timepoint.
  • FIG. 6 A-B depict transepithelial electrical resistance (TEER) measurements recorded throughout the experiment on days 2, 5, 6, 7 and post-inoculation.
  • TEER transepithelial electrical resistance
  • FIG. 7A-B depict cytokine levels as compared to the no bacteria control at 8 hours post-inoculation.
  • the term “and/or” includes any and all combinations of one or more of the associated listed items. Further, the singular forms and the articles “a”, “an” and “the” are intended to include the plural forms as well, unless expressly stated otherwise. It will be further understood that the terms: includes, comprises, including and/or comprising, when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. Further, it will be understood that when an element, including component or subsystem, is referred to and/or shown as being connected or coupled to another element, it can be directly connected or coupled to the other element or intervening elements may be present.
  • FIG. 1 shows a schematic diagram of an apparatus 10 for detecting interaction between a pathogen and a biological agent in a high throughput manner.
  • the pathogen is a virus.
  • the apparatus and methods described herein remain essentially unchanged when different kinds of pathogens are used.
  • the apparatus 10 is intended to maintain living cells on a platform 12 for extended periods.
  • the apparatus 10 includes, in addition to the platform 12, a source 14 of an input solution 16 that contains nutrients and other factors for promoting cell growth and maintenance, as well as factors that promote robust infectivity, such as bile, mucins, or trypsin.
  • a first pump 18 pumps this input solution 16 through the platform 12.
  • a second pump 22 pumps an output solution 24 out of the platform 12.
  • This output solution 24 includes waste products of cellular metabolism.
  • a suitable implementation of an apparatus 10 that can be used to maintain cells in a platform is a microfluidic system such as that disclosed in U.S. Patent No. 10,018,620 and U.S. Patent Application 2018/0142196, the contents of which are herein incorporated by reference.
  • the platform 12 is divided into different distinct interaction sites 26, 27, 28 that are isolated from each other and designed to support prolonged cell culture, the controlled delivery of infectious agents, and the monitoring of the biological entity interactions.
  • These interaction sites 26, 27, 28 define an interaction array 30. Although only a few such interaction sites 26, 27, 28 are shown, this is only to avoid visual clutter in the drawing. In practice, practical considerations will limit number of such interaction sites 26, 27, 28. However, in one preferred embodiment, there are ninety-six such interaction sites 26, 27, 28 per platform 12.
  • the illustrated platform 12 supports multiple growth formats. Some examples of such growth formats include growth at an air-liquid interface, growth of immersed cell monolayers, and even growth of suspended cells that do not require any surface attachment.
  • the apparatus 10 further includes an activity-detector 32 in communication with a data-processing system 33.
  • the activity-detector 32 obtains evidence indicative of the occurrence of an interaction between the viruses and biological agents that are disposed within the platform 12. The nature of the activity -detector 32 and precisely how these interactions are detected are both discussed below in detail.
  • the different interaction sites 26, 27, 28 are first seeded with different biological agents. Once the interaction sites 26, 27, 28 have been seeded, they are exposed to a pathogen solution 36. Such exposure can be carried out by a third pump 34 that pumps a pathogen solution 36 through the platform 12. This floods the interaction array 30 and thus exposes the biological agents within the interaction sites 26, 27, 28 to a suitable concentration of the pathogen. Alternatively, a pipette, or several pipettes in parallel, can drop pathogen solution 36 onto each interaction site 26, 27, 28. In the illustrated embodiment, the pathogen is a virus.
  • the platform 12 is seeded with different candidate host cells at different interaction sites 26, 27, 28. As a result, each interaction site 26, 27, 28 will have a different kind of cell growing within it.
  • the first and second pumps 18, 22 operate until cell growth is suitably established. They continue to operate throughout the procedure. In some embodiments, the interaction sites he on a first side of a semi-permeable membrane while the first and second pumps 18, 22 move fluid along a second side of the membrane. In such embodiments, the cells and the virus he on the first side of the membrane.
  • the virus may have no interaction with the cells.
  • the virus may infect the cell but fail to replicate.
  • the virus may infect the cell and replicate successfully.
  • infected cells lyse, thus releasing new viruses that can then infect neighboring cells, thus initiating a chain reaction. It is these cells that can be used for making larger quantities of viruses, which can then be used for vaccine production.
  • the activity-detector 32 observes a change in the way the medium at the interaction site 26, 27, 28 scatters light.
  • Other embodiments use
  • interferometry to detect changes in interference patterns that result from, for example, the presence of additional particles, such as virus particles.
  • additional particles such as virus particles.
  • the activity-detector 32 observes a change in the chemical composition of the solution at the interaction site 26, 27, 28. For example, it is possible to observe changes in concentration of ATP or other metabolites. This can be carried out using colorimetric, fluorescence, or luminescence assays.
  • one, or more of the biological or chemical entities comprising the interaction to be monitored can be detectably labeled with fluorescent tags or dyes.
  • fluorescent tags are suitable to specifically detect the interaction to be detected/followed and can be used along with an optical readout means (either integrated into the apparatus/platform or apart from the apparatus/platform) to track the interaction in real time through readout of fluorescent intensity and/or lifetime.
  • This embodiment provides a platform where tracking can occur at the rates required due to the close integration of the electronics as well as the use of fast LEDs and fast photodiodes instead of lamps and cooled CCD cameras.
  • a method for detecting which of several antimicrobial agents is effective against a particular pathogen can be carried out in an analogous manner.
  • the pathogen is a virus and the antimicrobial agent is an antibody
  • the biological agent consists of a cell and a candidate antibody.
  • the cell is one that is known to be a suitable host for the virus in question. A suitable procedure for identifying such a cell has already been described above.
  • the candidate antibodies differ from one interaction site to the next, but the cell type remains constant.
  • the first and second pumps 18, 22 operate until cell growth is suitably established and continue to operate throughout the procedure.
  • the cells are exposed to a pathogen solution 36.
  • a pathogen solution 36 Such exposure can be carried out by using a third pump 34 to flood the platform 12 with the pathogen solution 36.
  • one or more pipettes can be used to drop pathogen solution 36 at each interaction site 26, 27, 28.
  • the antibody that is present at the first interaction site 26 may fail to prevent infection.
  • the cell will lyse and spread infection.
  • the antibody present at the second interaction site 27 may be just right for preventing infection by that virus.
  • the activity-detector 32 can thus be used in a manner similar to that already described to provide early-detection of successful replication. This provides a basis for rapidly assessing effectiveness of particular antibodies.
  • the platform 12 is seeded with different biological agents at different interaction sites 26, 27, 28.
  • the biological agent consists of a cell and a candidate antimicrobial agent.
  • the cell is one that is known to be susceptible to being harmed by the pathogen in question. A suitable procedure for identifying such a cell can be readily adapted based on what has already been described above.
  • the candidate antimicrobial agents differ from one interaction site to the next, but the cell type remains constant.
  • the first and second pumps 18, 22 operate until cell growth is suitably established and continue to operate throughout the procedure.
  • the cells are exposed to a pathogen solution 36.
  • a pathogen solution 36 Such exposure can be carried out by using a third pump 34 to flood the platform 12 with the pathogen solution 36.
  • one or more pipettes can be used to drop pathogen solution 36 at each interaction site 26, 27, 28.
  • the antimicrobial agent that is present at the first interaction site 26 may fail to prevent harm to the cell.
  • the antimicrobial agent present at the second interaction site 27 may be just right for preventing harm to the cell from that pathogen.
  • Examples of structural changes include changes in the aggregation of matter at the interaction site.
  • Examples of changes in composition include changes in metabolite levels or changes in substances that are depleted or produced during replication.
  • Such changes may be in the intracellular medium or in the extracellular medium in the vicinity of the cell.
  • the structural changes or changes in composition can offer a clue to the fact that an antimicrobial agent has failed to prevent a pathogen from interacting with a cell.
  • the activity-detector 32 detects such changes.
  • the activity detector can be integrated into the apparatus.
  • the activity detector can comprise a separate means or device for a chemical or biological substance detection assay performed apart from the apparatus and the results correlated with the specific interaction point as well as the specific time-point.
  • chemical and biological assays are well-known to those of skill in the art.
  • a cytokine expression profile panel can comprise a biological assay as described in the Exemplification herein.
  • the activity-detector 32 can be used in a manner similar to that already described to provide early-detection of cellular harm caused by pathogens. This provides a basis for rapidly assessing effectiveness of particular antimicrobial agents.
  • a biological agent that consists of host cells and an antibody cocktail having a mixture of antibodies. In that case, if the cells in a first interaction site 26 die, one can infer that none of the antibodies in that first interaction site 26 were effective. If the cells in a second interaction site 28 live, one can infer that at least one of the antibodies in the antibody cocktail was effective. This method can also be used to identify cytotoxicity of antibody cocktails.
  • FIG. 2 shows steps in a process carried out by the apparatus of FIG. 1 to identify an interaction between a microbe and a biological agent.
  • the process begins with providing a platform 12 for supporting cell growth (step 40).
  • the platform 12 includes a plurality of interaction sites.
  • interaction sites 26, 27, 28 are described as being arranged as rows and columns of a rectangular interaction array 30, this particular arrangement is by no means required. What is required instead is a way to encode the identity of a biological agent at a particular interaction site 26, 27, 28. In a case in which the interaction sites 26, 27, 28 are fixed relative to some frame-of-reference, as shown in FIG. 1, a convenient way to encode this information is by the spatial position of the interaction site 26, 27, 28 in some coordinate system. Arranging interaction sites 26, 27, 28 in an interaction array 30 makes this particularly convenient.
  • a biological agent includes more than just cells.
  • a biological agent may be a combination of cells and antibodies, or a combination of cells and an antibody cocktail.
  • the process includes causing an input fluid to perfuse through the platform 12 (step 44).
  • the input fluid will contain nutrients and any other factors needed to promote cellular growth and maintenance.
  • the cells typically achieve confluency within twenty-four or forty- eight hours.
  • the process continues with a viral challenge (step 46). This permits interaction between the viruses and the various biological agents distributed among the interaction sites 26, 27, 28.
  • the platform 12 is monitored in real time for signs of such interaction.
  • evidence of such interaction is detected (step 48). Examples of such evidence include a change in composition of the medium within the interaction site.
  • activity -detector 32 Several embodiments of the activity -detector 32 are available, depending on the physical properties to be monitored. These include activity -detectors 32 that monitor impedance, transepithelial electrical resistance, glucose demand, acidity, alkalinity, and occurrence of redox reactions. Additional embodiments of activity detectors 32 include those that carry out biochemical assays of substances present in the interaction site 27 and optical assessments of cell morphology or intracellular activity at the interaction site 27.
  • An activity -detector 32 can also be configured to monitor more than one of the foregoing parameters rather than relying on only one of them.
  • Among the most useful activity detectors 32 are those that carry out metabolic assays for detecting early-stage infection across many classes of viruses and types of cells. Such assays are calibrated with baseline viral-infection screening data. The generation of such baseline screening data would include measuring a host cell’s phenotype during the course of an infection cycle. Such data often reveals a well-defined point in time at which one can safely say that there has been a virus-mediated change to the phenotype.
  • Such an activity detector 32 monitors the challenged cell’s phenotype in an effort to detect the occurrence of this point. Reliance on metabolic changes caused by infection permits such an activity detector 32 to detect the change early in the infection process. This provides a basis for obtaining a prompt indication of viral infection.
  • Real-time monitoring of metabolite level is particularly useful because viral infection changes the host’s cellular metabolism in a manner that promotes viral replication. Since viral replication requires additional energy, and since energy production is linked to metabolism, a sudden demand for energy will make itself apparent through a corresponding change in metabolism. In particular, the sudden demand for energy that arises from replication manifests itself in increased production and/or depletion of ATP. Thus, a sudden change in ATP concentration serves as a marker for viral replication.
  • an activity detector 32 that monitors metabolic activity monitors cellular ATP concentration using a luminescence-based assay.
  • the luminescent signal is proportional to the concentration of ATP.
  • Such an assay is also amenable to high-throughput screening.
  • real-time monitoring of ATP concentration permits detection of viral replication well in advance of the cytopathic effects that would normally announce such replication.
  • an ATP- luminescence phenotype screen may allow what is effectively real-time detection of viral infection. This significantly accelerates the screening process.
  • An activity detector 32 that implements an ATP-luminescence phenotype assay offers considerable sensitivity. In many cases, such an activity detector 32 is capable of measuring changes in cellular metabolism even when the number of cells is below the detection limits of standard fluorometric assays.
  • an activity detector 32 can instead implement an alternative metabolic assay to determine whether viral infection has occurred.
  • the activity detector 32 implements a fluorometric water-soluble redox indicator.
  • Other methods could be used to detect viral infection, including standard cell viability or cytotoxicity assays that depend on cytopathic effects, such as lactate dehydrogenase release or live-dead staining.
  • Other embodiments of the activity detector 32 monitor changes wrought by virus replication to optical properties of a medium. As a virus grows, certain biomolecules will be synthesized within a cell. These biomolecules will eventually assemble or aggregate to form a whole infectious virus. As this aggregation occurs, it leaves behind certain subtle clues. In particular, the aggregation locally modulates the refractive index in the cell and its surroundings.
  • the activity detector 32 directly detects this virus- induced modulation optically using a device that comprises a light source, such as a diode or laser, optics for focusing or shaping the light, and a detector or camera that interfaces with the platform 12.
  • a device that comprises a light source, such as a diode or laser, optics for focusing or shaping the light, and a detector or camera that interfaces with the platform 12.
  • Such activity detectors 32 include optical devices, such as fiber- optical or free-space optical devices, that directly characterize the growth of a virus at very early stages.
  • the activity detector 32 carries out interferometric measurements of the amplitude of the scattered light field. This is particularly useful for detecting particles that have a low refractive-index, such as viruses in aqueous solution.
  • the activity detector 32 carries out angle-resolved, low- coherence interferometry. Such an activity detector 32 measures angular distributions of back-scattered light and uses it to recover structural information about subsurface layers.
  • the activity detector 32 relies on optical diffraction tomography.
  • Such an activity detector 32 includes a Mach-Zehnder interferometer that characterizes complex optical fields.
  • the processor 33 uses this amplitude and phase delay information to reconstruct a three-dimensional map of the cell showing the modulation of refractive index at various locations within the cell.
  • Other embodiments of the activity-detector 32 rely on nanoparticles, fluorescent, luminescent, or colorimetric dyes to infer infection-induced changes in such features as a change in the potential across the membrane upon which the cells grow, a change in a particular metabolite concentration, a change in the concentration, amount, or identity of any one of a variety of biomolecules, including proteins and nucleic acids.
  • micro-carriers Upon identification of cell type for viral amplification, it becomes possible to adapt process protocols and small-scale stir-perfusion and rotating vessel bioreactors with micro-carriers to produce sufficient quantities of viral particles for all downstream platform applications, including animal studies.
  • An example of a suitable micro-carrier is that sold under the name CYTODEX(R) by GE Biologies.
  • EXEMPLIFICATION Acute pyelonephritis model
  • Fimbriae are surface-expressed appendages that mediate bacterial adherence to host cells and tissues.
  • P fimbriae encoded by the pap genes
  • UPEC uropathogenic E. coli
  • P fimbriae specifically interact with gly colipids that are expressed by erythrocytes and host kidney cells (Mulvey et al., 2000), and their attachment to host cells aids bacteria in withstanding the flow of urine.
  • Type 1 fimbriae encoded by the flm genes
  • Type 1 fimbriae may also play a role in upper urinary tract colonization despite the lack of mannosylated receptors on renal epithelia. It has been suggested that in the presence of fluid flow in the proximal tubule of a living kidney, both P and Type 1 fimbriae act synergistically to promote epithelial and inter-bacterial interactions, respectively, to withstand flow and enhance colonization (Melican et al,
  • Host immune response to bacterial urinary tract infections also appears to be influenced by fimbrial adhesion, which is believed to bring the bacterial endotoxin (lipopolysaccharide) into proximity with host cells, strongly inducing cytokine expression.
  • Model systems of UPEC infection of the kidney typically use murine models or in vitro human monolayer cultures. Many animal models do not possess the same receptor proteins required for colonization of human cells, nor the same cytokines.
  • a human organ system see e.g., U.S. Patent No. 10, 018,620, the teachings of which are incorporated by reference in their entirety) was used to assess the biological interactions/associations of UPEC bacteria in an in vitro model of human kidney proximal tubule infection— acute bacterial pyelonephritis.
  • the platform enabled testing of multiple fimbrial mutants of UPEC clinical isolates, in a more physiologically -relevant human tissue model, and in the presence of relevant fluid flow conditions experienced by the host cells and the infecting bacteria in the human renal proximal tubule.
  • Knowledge for culturing of the required cells within the device is known to those of skill in the art.
  • Fimbrial adhesion by UPEC is influenced by flow— a controllable feature of the device as described herein— enabling testing of the contribution of the two fimbrial types (P fimbriae, and Type 1 fimbriae) to colonization in the presence of flow.
  • flow a controllable feature of the device as described herein— enabling testing of the contribution of the two fimbrial types (P fimbriae, and Type 1 fimbriae) to colonization in the presence of flow.
  • Numerous clinical and/or phenotypic markers are known for both the host and pathogen, allowing us to make testable hypotheses. Taken together, these factors allowed the testing of the utility of the device and its physiological accuracy, to assess host-pathogen interactions in a well understood human tissue model as described above.
  • Kidney cells were co-cultured in cell culture devices as described in V edula et. al, 2017; U.S. Patent No. 10, 018,620; and U.S. Patent Application 2018/0142196.
  • plates were treated to permit growth of the cells.
  • Human microvascular endothelial cells hMVECs
  • RPTECs renal proximal tubular epithelial cells
  • RPTECs renal proximal tubular epithelial cells
  • Cells were counted to estimate loads prior to inoculation by the bacterial strains.
  • Cells were grown under fluid flow of 10 ul/min, which is comparable to that experienced in the kidney tubule (Vedula et al, 2017).
  • TEER is a quantitative measurement of barrier function and/ or tight j unction formation of cells in culture, which was used to determine whether barrier function or cell integrity was damaged as a result of the bacterial infection, via host cell lysis or exfoliation. Using a proprietary device and method, TEER was assessed throughout the experiment. The device was sterilized after all TEER readings.
  • Interleukin-6 Pro-inflammatory cytokine; upregulated in UPEC infection (Frendeus et al, 2001)
  • Interleukin-8 (IL-8): Chemotaxis of neutrophils to infection site; upregulated in UPEC infection (Agace et al, 1993; Frendeus et al, 2001)
  • MCP-l Monocyte chemoattractant protein 1
  • Interferon gamma IFN-g: Involved in immunity against viral and some bacterial infections (Khalil et al, 2000)
  • Tumor necrosis factor alpha (TNF-a): Expected to be secreted in response to bacterial LPS (Su et al, 2014)
  • TEER measurements were recorded throughout the experiment on Day s 2, 5, 6, 7 pre- and post-inoculation (Fig. 6A-D). Bladder cell exfoliation is known to occur in mice as a host defense mechanism against UPEC adhesion via Type 1 fimbriae (Mulvey et al, 2000). TEER measurements did not appear to significantly change over the course of our experiment, suggesting that the proximal tubule tissue barrier was not compromised under any of the conditions or with any of the strains, regardless of fimbrial phenotypes.
  • TNF-a levels appeared to increase compared to the no bacteria control, and may vary depending on the strain and MOI, although this would need to be repeated for statistical significance (Fig. 7A). IFN-g and MCP-l levels did not appear to be upregulated in response to UPEC bacteria, as levels did not significantly increase over the no bacteria control (Fig. 7A, and 7B). [00132] References

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Abstract

L'invention concerne un procédé d'identification d'une interaction entre un agent pathogène et un agent biologique, ce procédé comprenant les étapes consistant à : fournir une plate-forme de support de croissance cellulaire ; ensemencer différentes sites d'interaction sur la plate-forme avec différents agents biologiques ; perfuser la plate-forme avec un fluide qui transporte des substances destinées à favoriser la croissance et la maintenance de ces cellules ; exposer tous les sites d'interaction à une solution contenant des virus, et détecter une preuve révélatrice de l'interaction, cette preuve comprenant une preuve révélatrice d'un changement dans la structure ou la composition d'un milieu au niveau du site d'interaction. L'agent biologique comprend des cellules seules ou des cellules avec une autre substance.
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Citations (5)

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WO2010018499A1 (fr) * 2008-08-11 2010-02-18 Koninklijke Philips Electronics N.V. Appareil et procédé de test de sensibilité cellulaire
US20180142196A1 (en) 2016-11-23 2018-05-24 The Charles Stark Draper Laboratory, Inc. Bi-layer multi-well cell culture platform
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US6197575B1 (en) * 1998-03-18 2001-03-06 Massachusetts Institute Of Technology Vascularized perfused microtissue/micro-organ arrays
US20040018485A1 (en) * 1999-04-15 2004-01-29 Ilya Ravkin Multiplexed analysis of cells
WO2010018499A1 (fr) * 2008-08-11 2010-02-18 Koninklijke Philips Electronics N.V. Appareil et procédé de test de sensibilité cellulaire
US10018620B2 (en) 2014-04-16 2018-07-10 The Charles Stark Draper Laboratory, Inc. Microfluidic tissue model
US20180142196A1 (en) 2016-11-23 2018-05-24 The Charles Stark Draper Laboratory, Inc. Bi-layer multi-well cell culture platform

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FRENDEUS B; WACHTLER C; HEDLUND M; FISCHER H; SAMUELSSON P; SVENSSON M; SVANBORG C: "Escherichia coli P fimbriae utilize the Toll-like receptor 4 pathway for cell activation", MOL MICROBIOL., vol. 40, no. 1, 2001
HEDLUND, M.; FRENDEUS, B.; WACHTLER, C.; HANG, L.; FISCHER, H.; SVANBORG, C.: "Type 1 fimbriae deliver an LPS- and TLR4-dependent activation signal to CD14-negative cells", MOL MICROBIOL., vol. 39, no. 3, 2001, XP002316200, DOI: doi:10.1046/j.1365-2958.2001.02205.x
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