Cell analysis

Abstract

The disclosure concerns methods for the analysis and characterisation of cells such as the identification of different cell types using impedance or dielectric spectroscopy in cell culture medium.

Description

[0001] Cell Analysis

[0002] Field of the Invention

[0003] The disclosure concerns methods for the analysis and characterisation of cells such as the identification of different cell types using impedance or dielectric spectroscopy in cell culture medium.

[0004] Background to the Invention

[0005] Flow Cytometry and Fluorescence Activated Cell Sorting (FACS) allows rapid analysis of cells and has applications in a variety of disciplines such as immunology, molecular biology and virology. For example, Flow Cytometry can be used to analyse a mixed population of cells expressing specific antigens on the cells surface, other applications include the detection of apoptosis and further, FACS can be used to separate and isolate cells such as tumour cells, stem cells or other particles. Typically, FACS uses flow cytometry combined with fluorescent dyes conjugated to an antibody that bind to a specific cell protein of interest, for example a cell membrane located receptor, characteristic of the cell. The stained cells are then passed through a flow cell, where they are illuminated by a laser beam. As the cells pass through the laser, their fluorescence is detected and analysed in real-time. Based on their fluorescent properties, cells can be sorted and separated for further analysis. Other methods include the use of non-fluorescent dyes which bind to different structures of the cells such as viability dyes which bind to amines to determine if the cell membrane is intact or dyes to detect signalling such as calcium indicator dyes. Although Flow cytometry and FACs provide a rapid multiparametric analysis, the method requires the use of dyes to identify the specific characteristics of the cells which is complex and time consuming leading to labour intensive data interpretation. Moreover, in order to prepare the cells for the analysis, additional handling of the cells and change of buffer is required which can lead to changes in cell characteristics, cell lysis and inaccurate measurements.

[0006] There is a need for a simple, label free method for the analysis of cells to enable the identification of cell types and changes in cellular phenotype.

[0007] An alternative, label free method for analysing cells utilises impedance or dielectric spectroscopy to measure characteristics of a cell population. Impedance or dielectric spectroscopy involves applying an electrodynamic field to a solution containing cells and measuring the changes to the field due to the presence of the cell e.g., caused by the complex electrical permittivity of a cell. When a cell is measured by impedance, the fluid medium surrounding the cell is also measured. The effect of measurement of the surrounding fluid medium is addressed by carrying out two measurements at the same time, namely a first measurement of a cell and fluid medium holding the cell, and a second measurement of fluid medium without a cell. The difference between the first and second measurements is then determined to provide a measurement of the cell. The measurement apparatus therefore comprises a first measurement component which makes the first measurement and a second measurement component which makes the second measurement, the first and second measurement components operate at the same time. Where measurement involves applying a stimulus to a sample and measuring a response to the stimulus, such as in impedance or dielectric spectroscopy, the stimulus is usually of considerably greater amplitude than the amplitude of the response to the stimulus.

[0008] An example of the use of impedance or dielectric spectroscopy is disclosed in WO2015 / 001355, the content of which is incorporated by reference in its entirety, which describes a spectroscopy system that allows label-free cell analytics for the detection and analysis of cells. The system enables the user to identify cells based on their intrinsic dielectric profile, providing them with a unique identifier for subsequent downstream analysis and characterisation, without cell labelling or lasers. PCT / GB2024 / 051121 and PCT / GB2024 / 051222, the content of each of which is incorporated by reference in their entirety, each disclose an improved spectroscopy system using high bandwidth allowing the analysis of many different characteristics of a cell at a time.

[0009] This disclosure relates to a method for the multi-parametric analysis of cells in the field of molecular biology, immunology, microbiology, and cell heath. The present disclosure provides a rapid and simple label free method to assess the characteristics of cells such as state of differentiation, cell viability e.g., apoptotic state, identification of different cell types, cells expressing different proliferation markers, analysis of the cell cycle in a cell culture medium or monitoring cells as they grow in culture over short or prolonged periods to determine growth consistency or stability.

[0010] Statements of Invention

[0011] According to an aspect of the invention there is provided a method for the identification and analysis of cells under test of more than one cell type in one or more cell culture media using impedance or dielectric spectroscopy comprising the steps: i) providing an electric stimulus signal having at least one component at a first frequency to at least one stimulus electrode, such that the at least one stimulus electrode generates a pre-determined, electrodynamic field including the first frequency that is applied to a cell under test of a first cell type in a cell culture medium; ii) sensing a response electrodynamic field by means of at least one sensing electrode and providing a corresponding electric response signal to a sensing circuit, and obtaining a first output signal corresponding to said cell under test of the first cell type; iii) providing said electric stimulus signal to at least one stimulation electrode, such that the at least one stimulus electrode generates said pre-determined, electrodynamic field that is applied to a cell under test of a second, different cell-type in a cell culture medium; iv) sensing a response in the electrodynamic field by means of at least one sensing electrode and providing a corresponding electric response signal to the sensing circuit, and obtaining a second output signal corresponding to said different cell type; v) comparing the first and second output signals to determine a measure of differentiation between said first and second cell-type; wherein the electric stimulus signal and the electrodynamic field has at least one frequency component that is greater than 0.15 GHz.

[0012] According to an aspect of the invention there is provided a method for the measurement and analysis of at least a first eukaryotic cell type, or subcellular part thereof, and a second cell type, or subcellular part thereof, under test in one or more cell culture media using impedance or dielectric spectroscopy comprising the steps: i) providing measurement apparatus comprising a first stimulus electrode and a first sensing electrode providing a first measurement capacitor, operative through a first part of a fluid passageway or a first fluid passageway; a second stimulus electrode and a second sensing electrode providing a second measurement capacitor, operative through a second part of a fluid passageway or a second fluid passageway; the first sensing electrode being electrically connected to the second sensing electrode; a stimulation apparatus electrically coupled to the first and second stimulus electrodes; and a sensing circuit having an input coupled to the electrical connection between the first and second sensing electrodes, and an output for providing an output signal; ii) providing first and second electric stimulus signals having at least one component at a first frequency simultaneously to the first and second stimulus electrodes respectively, the first and second electric stimulus signals having the same form and opposite polarity, such that the first and second stimulus electrodes generate a pre-determined, electrodynamic field including the first frequency that is applied to a cell under test of a first eukaryotic cell type in a cell culture medium; iii) obtaining from the output of the sensing circuit a first output signal corresponding to said cell under test said first eukaryotic cell type; iv) providing said first and second electric stimulus signals simultaneously to the first and second stimulation electrodes respectively, such that the first and second stimulus electrodes generate said pre-determined, electrodynamic field that is applied to a cell under test of a second, different cell-type in a cell culture medium; v) obtaining from the output of the sensing circuit a second output signal corresponding to said different cell type; vi) comparing the first and second output signals to determine a measure of differentiation between said first and second cell-type; wherein the electric stimulus signal and the electrodynamic field has at least one frequency component that is greater than 0.15 GHz.

[0013] In a preferred method of the invention said at least one frequency component is between 0.15GHz and 10GHz. The at least one frequency component may be between 0.15GHz and 3GHz

[0014] “Cell-type” is defined as a cell-type that can be obtained from the same or different species but is different either genetically or phenotypically. For example, comparison can be made between cells that are genetically modified by introduction of nucleic acid that alters the phenotype of the cell when compared to a non-genetically modified cell, e.g., by introduction of vector nucleic acid, viral vector nucleic acid or viral nucleic acid. A further example is the comparison of cells that are genetically the same but have been exposed or modified by an agent that materially alters the phenotype of a cell when compared to a cell that has not been exposed to the agent. A further example includes a cell that is undergoing differentiation from a first cell type to a second or subsequent cell type, for example the differentiation of a stem cell such as an embryonic stem cell, progenitor cell or IPS cell to a more differentiated cell type. Alternatively, cell type includes cells that are altered from a differentiated cell type to a less differentiated cell type as for example the de-differentiation of, for example, a fibroblast to a less differentiated lineage restricted or pluripotent cell type. “Cell type” also encompasses the analysis of cells undergoing growth in culture from an early grow phase though to exponential and stationary growth phases to monitor phenotype, particularly the viability of said cells in culture during growth phases. In addition, “cell-type” can mean a comparison between cells in a mixed culture to identify and analyse changes in gene expression and phenotype to monitor cell proliferation during phases of growth. "Cell type” can also refer to cells from the same populations that are grown over short or prolonged periods of time to determine whether or not they maintain consistent phenotypes or stability profiles over time when comparing cells from the start to the end of the culture period. Moreover, “cell type” can mean a comparison of one cell type and a second or additional cell type that is infected by an adventitious agent such as a virus or other intracellular pathogens such as pathogenic bacteria. The disclosure also include the analysis and comparison of subcellular structures within cell-type that are analysed, for example the analysis of organelles such as endoplasmic reticulum, Golgi apparatus, mitochondria and nuclear / nucleolar organelles.

[0015] In a preferred method of the invention said more than one cell type is one, two, three, or more cell types in a mixed culture.

[0016] In a preferred method of the invention said first and second cell-type is contained in the same cell culture medium as separate cultures.

[0017] In an alternative preferred method of the invention said first and / or second cell type is a mixed culture contained in the same cell culture medium.

[0018] In a preferred method of the invention said first and / or second cell type are eukaryotic cells.

[0019] In a preferred method of the invention said first and / or second eukaryotic cell type is selected from the group: a mammalian cell, a plant cell an insect cell or a fungal cell.

[0020] In a preferred method of the invention said first and / or second mammalian cell is a non-human mammalian cell.

[0021] In an alternative preferred method of the invention said first and / or second mammalian cell is a human cell. In a preferred method of the invention said first and / or second mammalian cell is a cancer cell.

[0022] As used herein, the term “cancer” refers to cells having the capacity for autonomous growth, i.e., an abnormal state or condition characterized by rapidly proliferating cell growth. The term is meant to include all types of cancerous growths or oncogenic processes, metastatic tissues or malignantly transformed cells, tissues, or organs, irrespective of histopathologic type or stage of invasiveness. The term “cancer” includes malignancies of the various organ systems, such as those affecting, for example, lung, breast, thyroid, lymphoid, gastrointestinal, and genito-urinary tract, as well as adenocarcinomas which include malignancies such as most colon cancers, renal-cell carcinoma, prostate cancer and / or testicular tumours, non-small cell carcinoma of the lung, cancer of the small intestine and cancer of the esophagus. The term “carcinoma” is art recognized and refers to malignancies of epithelial or endocrine tissues including respiratory system carcinomas, gastrointestinal system carcinomas, genitourinary system carcinomas, testicular carcinomas, breast carcinomas, prostatic carcinomas, endocrine system carcinomas, and melanomas. Exemplary carcinomas include those forming from tissue of the cervix, lung, prostate, breast, head and neck, colon and ovary. The term “carcinoma” also includes carcinosarcomas, e.g., which include malignant tumours composed of carcinomatous and sarcomatous tissues. An “adenocarcinoma” refers to a carcinoma derived from glandular tissue or in which the tumor cells form recognizable glandular structures. The term “sarcoma” is art recognized and refers to malignant tumors of mesenchymal derivation. Alternatively, said cancer cell is a cancer stem cell. The concept of a cancer stem cell within a more differentiated tumour mass, as an aberrant form of normal differentiation, has gained acceptance over the current stochastic model of oncogenesis, in which all tumour cells are equivalent both in-growth and tumour-initiating capacity.

[0023] In a preferred method of the invention said first and / or second mammalian cell is an apoptotic cell.

[0024] In a preferred method of the invention said first and / or second mammalian cell is a necrotic cell.

[0025] In a further preferred method of the invention said first and / or second mammalian cell is a stem cell.

[0026] In a preferred method of the invention said stem cell is a pluripotent stem cell, for example an embryonic stem (ES) cell or embryonal germ (EG) cell or an induced pluripotent stem cell. In a preferred method of the invention said stem cell is a lineage restricted stem cell, e.g., a multipotent stem cell.

[0027] Preferably said lineage restricted stem cell is selected from the group: haemopoietic stem cells; neural stem cells; bone stem cells; muscle stem cells; mesenchymal stem cells; trophoblastic stem cells; epithelial stem cells (derived from organs such as the skin, gastrointestinal mucosa, kidney, bladder, mammary glands, uterus, prostate and endocrine glands such as the pituitary); endodermal stem cells (derived from organs such as the liver, pancreas, lung and blood vessels); muscle cell e.g. cardiomyocyte.

[0028] The invention allows monitoring and analysis of cells undergoing differentiation from one cell type to a second or subsequent cell type of different phenotype. For example, the differentiation of haemopoietic cells such as haemopoietic stem cells into various blood cell lineages. Haemopoietic stem cells have the capability of differentiating into all the differentiated cells that comprise blood cells including myeloid-lineage (e.g., granulocytes, monocytes, megakaryocytes and dendritic cells) and lymphoid-lineage cells (e.g., T cells, B cells and natural killer cells).

[0029] Typical examples include the differentiation of pluripotent stem cells or haemopoietic cells such as macrophages. WO2024 / 038182, the content of which is incorporated by reference in its entirety, discloses engineered stem cells that are modified to reduce or exclude expression of HLA genes (HLA1 and / or HLA2) thereby forming hypoimmunogenic stem cells that are differentiated into hypoimmunogenic macrophages useful in the treatment of inflammatory conditions. The differentiation of stems cells to macrophages is known and disclosed in WO2021 / 240162 the content of which is incorporated by reference in its entirety. A further example is provided by WO2024 / 074376, the content of which is incorporated by reference in its entirety, which discloses monocyte derived macrophages that are engineered to express cytokines such as IL-10 and / or proteases such as matrix metalloprotease 9 (MMP9) or are derived from IPs cells similarly modified to express IL-10 and / or MMP9. WO2024 / 068728, the content of which is incorporated by reference in its entirety, discloses engineered macrophages expressing MMP9 and / or MMP12.

[0030] In a preferred method of the invention said first and / or second multipotent stem cell is a haemopoietic stem cell. In a preferred method of the invention said first and / or second haemopoietic stem cell is a monocyte capable of differentiation into a macrophage. Preferably, said haemopoietic stem cell is obtained from a human subject.

[0031] In an alternative preferred method of the invention said first and / or second cell is a differentiated haemopoietic cell obtained from a human subject.

[0032] Differentiated haematopoietic cells are all blood cells and the cells that produce them and are broadly categorized into myeloid and lymphoid lineages. Myeloid cells include red blood cells, platelets, monocytes, and granulocytes (neutrophils, eosinophils, and basophils). Lymphoid cells include T cells, B cells, and natural killer (NK) cells. Dendritic cells arise from both myeloid and lymphoid progenitors, while mast cells are of myeloid origin.

[0033] In a preferred method of the invention said cell culture medium is an apheresis product obtained from a subject.

[0034] Apheresis is a procedure that separates and collects specific components of blood, returning the remaining blood to the patient. The application of apheresis is for both collecting blood components for transfusion and removing harmful components from the blood to treat various diseases. Blood is drawn from a patient's vein and passed through a device that separates the blood into its components, such as red blood cells, white blood cells, platelets, and plasma. The desired component is collected or removed, while the remaining blood is returned to the patient. Apheresis is used to collect specific blood components, such as platelets or stem cells, for transfusion or other applications. Apheresis can be of different types and include platelet apheresis: Collects platelets red cell exchange, plasma exchange and low-density lipoprotein (LDL) apheresis and also includes the separation and isolation of haematopoietic cells and haematopoietic stem cells.

[0035] In a preferred method of the invention said first and / or second mammalian cell is infected with a pathogenic microbe or virus.

[0036] In a preferred method of the invention said first and / or second mammalian cell is selected from the group: THP-1 cell, Chinese Hamster Ovary cell, Jurkat cell, HEK293 cell, NSO cell and CAP cell.

[0037] In an alternative preferred method of the invention said first and / or second cell is a plant cell. In a preferred method of the invention said first and / or second plant cell is obtained from a plant selected from the group: corn (Zea mays), canola (Brassica napus, Brassica rapa ssp.), alfalfa (Medicago sativa), rice (Oryza sativa), rye (Secale cerale), sorghum (Sorghum bicolor, Sorghum vulgare), sunflower (helianthus annuas), wheat (Tritium aestivum) and soybean (Glycine max) Alternatively, plant cells of the present invention are obtained from oil-seed plants including olive, cotton, soybean, safflower, sunflower, maize, alfalfa, palm and coconut.

[0038] In a preferred method of the invention said first and / or second cell is a microbial cell.

[0039] Preferably, said microbial cell is a eukaryotic microbial cell, such as a fungal cell or algal cell.

[0040] Preferably, fungal cell is selected from the group consisting of yeast: Saccharomyces cerevisae, Schizosaccharomyces pombe Pichia pastoris, Aspergillus spp [e.g A.niger], Kluyveromyces lactis and Trichoderma reesei and Yarrowia lipolytica.

[0041] In an alternative preferred method of the invention said microbial cell is a prokaryotic microbial cell, such as a bacterial cell.

[0042] In a preferred method of the invention said first and / or second cell is a transgenic cell.

[0043] In a preferred method of the invention said first and / or second cell is a transfected mammalian cell.

[0044] In a preferred method of the invention said first and / or second cell is a mammalian cell transfected with a viral based vector.

[0045] In a preferred method of the invention said first and / or second cell is transfected to express a recombinant polypeptide or peptide.

[0046] In a preferred method of the invention said first and / or second cell is transfected to express a recombinant antibody or antibody fragment.

[0047] In an alternative preferred method of the invention said first and / or second cell is transfected to express a pharmaceutically active polypeptide or peptide.

[0048] In a preferred method of the invention said first and second cell is a transfected mammalian cell. Preferably, said transfected mammalian cell is a Chinese Hamster Ovary cell. Alternatively, said transfected mammalian cell is a HEK cell.

[0049] Viruses are commonly used as vectors for the delivery of exogenous genes. Commonly employed vectors include recombinantly modified enveloped or non-enveloped DNA and RNA viruses, for example baculoviridae, parvoviridae, picornoviridae, herpesveridae, poxviridae, adenoviridae, picornnaviridae or retroviridae. Chimeric vectors may also be employed which exploit advantageous elements of each of the parent vector properties (See e.g., Feng, et al (1997) Nature Biotechnology 15:866-870). Such viral vectors may be wild-type or may be modified by recombinant DNA techniques to be replication deficient, conditionally replicating or replication competent. Conditionally replicating viral vectors are used to achieve selective expression in particular cell types. Examples of conditionally replicating vectors are described in Pennisi, E. (1996) Science 274:342-343; Russell, and S.J. (1994) Eur. J. of Cancer 30A(8):1165-1171.

[0050] In a preferred embodiment of the invention said viral based vector is an adenovirus vector.

[0051] In a preferred embodiment of the invention said viral based vector is an adeno-associated virus [AAV],

[0052] In a preferred embodiment said AAV based vector is selected from the group consisting of: AAV2, AAV3, AAV6, AAV13; AAV1 , AAV4, AAV5, AAV6, AAV9 and rhAAVIO.

[0053] In a preferred embodiment of the invention said AAV vector is based on a single stranded AAV virus.

[0054] In an alternative embodiment of the invention said AAV vector is based on a self- complementary AAV virus.

[0055] Naturally occurring AAV serotypes typically comprise a single stranded genome which during natural infection is replicated to form a double stranded AAV viral genome. This is a rate limiting step in AAV replication and expression. A recombinant form of AAV is referred to as self-complementary AAV which comprise both a sense and antisense genomic strands that are adapted for immediate expression and replication. In an alternative preferred embodiment of the invention said viral based vector is a lentivirus- based vector.

[0056] Lentiviral based vectors have properties that confer advantageous properties that make them suitable for gene therapy applications. Lentiviral vectors can integrate their genetic material into the host cell's genome, unlike some other viral vectors that only exist as episomes. A key advantage is their ability to infect and integrate into both dividing and non-dividing cells. Lentiviral vectors can accommodate relatively large amounts of genetic material (up to 8-12 kb). The integration into the host genome ensures stable and long-term expression of the delivered nucleic acid.

[0057] In a preferred embodiment of the invention said first and / or second mammalian cell is a Human Embryonic Kidney (HEK) cell.

[0058] In an alternative preferred embodiment of the invention said first and / or second mammalian cell is a Chinese Hamster Ovary cell.

[0059] In a preferred method of the invention said method compares transfection efficiency by said viral based vector between said first and / or second mammalian cell.

[0060] In an alternative preferred method of the invention said method compares the production of exosomes between said first and / or second mammalian cell before or after transfection with said viral based vector.

[0061] Predicting transfection efficiency remains a key challenge in viral based vector production and is particularly problematic with reference to lentiviral based vector (LVV) production and gene therapy manufacturing. Despite advancements in transfection reagents, plasmid design, and process control, reliably predicting transfection outcomes remains difficult — especially in scalable, GMP-compliant environments where consistency and reproducibility are critical. Furthermore, exosome contamination is a major problem in viral based vector production and is particularly acute in LW manufacturing. Exosomes, which share physical and biochemical properties with LWs, are inadvertently co-purified during production. Their presence reduces vector purity and yield, affects transduction efficiency, and introduces immunogenic risks, ultimately impacting manufacturing success and therapeutic outcomes. These problems are addressed by the current disclosure which enables the analysis of both transfection efficiency and exosome contamination of compositions comprising viral based vectors. In a preferred embodiment of the invention said sample comprises or consists of cell culture medium, buffer and a biological sample such as a blood, urine or sputum sample.

[0062] According to a further aspect of the invention there is provided a method for the measurement and analysis of at least a one prokaryotic cell type, or subcellular part thereof, and a second cell type, or subcellular part thereof, under test in one or more cell culture media using impedance or dielectric spectroscopy comprising the steps: i) providing measurement apparatus comprising a first stimulus electrode and a first sensing electrode providing a first measurement capacitor, operative through a first part of a fluid passageway or a first fluid passageway; a second stimulus electrode and a second sensing electrode providing a second measurement capacitor, operative through a second part of a fluid passageway or a second fluid passageway; the first sensing electrode being electrically connected to the second sensing electrode; a stimulation apparatus electrically coupled to the first and second stimulus electrodes; and a sensing circuit having an input coupled to the electrical connection between the first and second sensing electrodes, and an output for providing an output signal; ii) providing first and second electric stimulus signals having at least one component at a first frequency simultaneously to the first and second stimulus electrodes respectively, the first and second electric stimulus signals having the same form and opposite polarity, such that the first and second stimulus electrodes generate a pre-determined, electrodynamic field including the first frequency that is applied to a cell under test of a first prokaryotic cell type in a cell culture medium; iii) obtaining from the output of the sensing circuit a first output signal corresponding to said cell under test of the first prokaryotic cell type; iv) providing said first and second electric stimulus signals simultaneously to the first and second stimulation electrodes respectively, such that the first and second stimulus electrodes generate said pre-determined, electrodynamic field that is applied to a cell under test of a second, different prokaryotic cell-type in a cell culture medium; v) obtaining from the output of the sensing circuit a second output signal corresponding to said different cell type; vi) comparing the first and second output signals to determine a measure of differentiation between said first and second cell-type; wherein the electric stimulus signal and the electrodynamic field has at least one frequency component that is greater than 0.15 GHz.

[0063] In a preferred method of the invention said at least one first cell type is a prokaryotic cell type and said second cell type is a prokaryotic cell type.

[0064] In an alternative preferred method of the invention said at least one first cell type is a prokaryotic cell type and said second cell type is a eukaryotic cell type.

[0065] In a preferred method of the invention said first cell type is a prokaryotic cell type and said second cell type is a microbial eukaryotic cell type.

[0066] In a further preferred method of the invention said eukaryotic microbial cell type is a fungal cell type.

[0067] In a preferred method of the invention said prokaryotic cell is a bacterial cell.

[0068] In a preferred method of the invention, the electric stimulus signal has a plurality of components at different frequencies, such that the at least one stimulus electrode generates a pre-determined, electrodynamic field including the plurality of different frequencies that is applied to the cells under test in one or more cell culture media. The electric stimulus signal and hence the pre-determined, electrodynamic field may comprise a signal packet including the plurality of components at different frequencies, with at least one signal packet including the plurality of components at different frequencies being applied to each cell to be measured.

[0069] In a preferred method of the invention, the electric stimulus signal comprises a pseudo-random binary sequence having a length and data rate that provide the pre-determined, electrodynamic field with a range of different frequencies. The pseudo-random binary sequence is preferably an m-sequence.

[0070] In a preferred method of the invention, the output signal of each cell measurement comprises a point or an array in multidimensional space for that particular cell. The output signal for a cell population may therefore comprise a multidimensional array. The comparison between the first and second output signals to determine a measure of differentiation between said first and second cell-type may comprise a comparison of a point or vector in multidimensional space for each cell. The comparison of cell populations relative to each other may include comparative statistic for high dimensional data, such as a modified Chi square or Hotelling’s statistics.

[0071] In a preferred method of the invention, the electrodes are exposed to and conduct into the cell culture medium.

[0072] In a preferred method of the invention, the electrodes and the sensing circuit are each part of an integrated circuit including an electrode array, the integrated circuit comprising layers of semiconductor.

[0073] In a preferred method of the invention, the electrodes are exposed to and conduct into the cell culture medium. For example, the integrated circuit may comprise an outermost passivation layer, e.g. a silicon nitride layer, that does not extend over the electrodes, such that the electrodes are exposed to and conduct into the cell culture medium.

[0074] Preferably, measurement may comprise: a fluid passageway for a fluid medium and any cells therein; at least one stimulus electrode and at least one sensing electrode providing at least one measurement capacitor, operative through at least one part of the fluid passageway; a stimulation apparatus electrically coupled to the at least one stimulus electrode and applying an electric stimulus signal to the at least one stimulus electrode; and a sensing circuit having an input coupled to the at least one sensing electrode, and an electric response signal generated at an output.

[0075] The electric stimulus signal and hence the pre-determined, electrodynamic field may comprise a signal packet, with at least one signal packet being applied to each cell to be measured. Where more than one signal packet of the electric stimulus signal and hence the predetermined, electrodynamic field is applied to the material to be measured, the signal packets may be applied sequentially. The apparatus is preferably arranged to allow only one cell to flow across a measurement capacitor at a time.

[0076] The electrodes may be generally planar in form. The electrodes may be generally cuboidal, and the operative surfaces of the electrodes may be square or rectangular, but other shapes may be chosen. The operative surface of each of the electrodes may be substantially flat. The electrode may comprise a continuous operative surface. Alternatively, the electrode may comprise a discontinuous operative surface formed of a plurality of separate conductive elements, eg a regular array of conductive elements that together define the electrode. The separate conductive elements may be separated by a dielectric material.

[0077] The at least one stimulation electrode and the at least one sensing electrode may be provided on an exposed surface of a semiconductor and may be formed in an integrated circuit formed by a semiconductor fabrication process, such as CMOS. The surfaces of the electrodes that contact the analyte may be treated to protect them from corrosion, for example with noblemetal deposition or metal removal. In one embodiment, a CMOS chip comprising metal electrodes is treated to remove the metal electrodes and expose the metal vias that connect metal layers within the chip and extend through dielectric layers. The exposed vias, previously under each metal electrode, thereby form an array of discrete conductive elements. Each array of vias, corresponding to a removed metal electrode, may therefore constitute an electrode the apparatus.

[0078] The electrodes of the measurement capacitor may be disposed on or towards a side of the flow passageway. The electrodes of the measurement capacitor may be disposed side by side. Such a same side disposition may be appropriate where the cell stimulation apparatus is comprised in a planar semiconductor integrated circuit, such as a CMOS integrated circuit.

[0079] The at least one stimulation electrode and the at least one sensing electrode may be arranged with their operative surfaces in a generally planar arrangement, e.g. side-by-side. The operative surfaces of each of the first and second measurement capacitors may lie in substantially the same plane. The fluent material and any cell therein may be disposed adjacent to the operative surfaces of the electrodes. The electrodes of the measurement capacitor may take the form of an electrode array, which is formed on a surface of a semiconductor device. The apparatus may comprise a plurality of electrode arrays, i.e., a plurality of measurement capacitors.

[0080] In preferred embodiments, the biological measurement apparatus comprises: a first stimulus electrode and a first sensing electrode providing a first measurement capacitor, operative through a first part of the fluid passageway or a first fluid passageway; a second stimulus electrode and a second sensing electrode providing a second measurement capacitor, operative through a second part of the fluid passageway or a second fluid passageway; the first sensing electrode being electrically connected to the second sensing electrode; the stimulation apparatus being electrically coupled to the stimulus electrodes and simultaneously applying first and second electric stimulus signals to the first and second stimulus electrodes respectively, the first and second electric stimulus signals having the same form and opposite polarity; and the sensing circuit having an input coupled to the electrical connection between the first and second sensing electrodes, and an electric response signal generated at an output.

[0081] The electrical connection between the first sensing electrode and the second sensing electrode may be insulated from the flow passageway.

[0082] Since the stimulation circuit simultaneously applies first and second stimulus signals to the first and second stimulus electrodes respectively, with the first and second stimulus signals being of the same form and of opposite polarity, the first and second measurement capacitors have common responses of opposite polarity to the first and second stimuli by way of the fluid medium that is common to their dielectrics. The common responses of opposite polarity result in a net zero signal at the electrical coupling between the first and second measurement capacitors. Where a cell in the fluid medium affects the dielectric of one of the measurement capacitors, the effect of the cell is thus present at the electrical coupling between the first and second measurement capacitors.

[0083] The present biological measurement apparatus therefore obviates the need for the two measurement circuits that is conventional in the prior art. Instead, there is one measurement circuit, which reduces the problems associated with a mismatch between the paths of two measurement circuits in a differential measurement. Further to this, one measurement path according to the invention means half the noise of the conventional approach which has two measurement paths. In addition, since the output signal in the present invention is a smaller signal associated with the effect of the cell, rather than the effect of the cell and the fluid medium in the prior art approach, means measurement of the response to the at least one cell and subsequent processing is much less affected by non-linearity in the measurement and processing path.

[0084] The measurement apparatus may be configured to provide the first measurement capacitor with fluid medium in the flow passageway, but no cell, as a complex dielectric between the first stimulus electrode and the first sensing electrode of the first measurement capacitor. The measurement apparatus may be configured to provide the second measurement capacitor with fluid medium and at least one cell in the flow passageway as a complex dielectric between the second stimulus electrode and the second sensing electrode of the second measurement capacitor.

[0085] The flow passageway may direct the fluid material and any cells therein over both the first and second measurement capacitors. If only one cell passes the first and second measurement capacitors at a time, the measurement apparatus may be configured to measure the cell whether it passes over the first measurement capacitor or the second measurement capacitor.

[0086] Alternatively, the measurement apparatus may be configured to direct fluid medium that does not contain cells over the first measurement capacitor and fluid medium that does contain cells over the second measurement capacitor. This may be achieved by applying a force to the cells in a single flow passageway, such that the cells are directed over the second capacitor, for example using hydrodynamic focussing, di-electrophoresis focusing, acoustic focusing or inertial focusing. The measurement apparatus may have two flow passageways, eg capillaries, a first flow passageway directing fluid medium not containing cells over the first measurement capacitor and a second flow passageway directing fluid medium containing cells over the second measurement capacitor. In this embodiment, the fluid medium not containing cells may be stationary over the first measurement capacitor during measurement.

[0087] As the first and second electric stimulus signals provided to the first and second stimulus electrodes respectively are identical, but have an opposite polarity, and the dielectric between the electrodes of each measurement capacitor is the same when no biological cell is present in the fluid medium, the response signals provided by the sensing electrodes to the electrical connection therebetween, and hence to the coupling with the output circuit, will cancel each other out and a net zero output will be obtained.

[0088] When a cell is located adjacent to one of the measurement capacitors, but there is no cell present adjacent to the other measurement capacitor, one of the measurement capacitors will have both a cell and the fluid medium as a dielectric, whereas the other measurement capacitor will have the fluid medium, but no cell, as a dielectric. The presence of the cell will cause the response signals provided by the sensing electrodes to the electrical connection therebetween, and hence to the coupling with the output circuit, to be different, such that a non-zero difference caused by the cell will be obtained as at output.

[0089] The sensing circuit may include a buffer circuit and may be configured to compare the signal obtained from the electrical connection between the first and second sensing electrodes with a reference signal. The output signal is processed to determine one or more properties of a biological cell sensed by the measurement capacitor.

[0090] The first and second measurement capacitors may have operative surfaces configured to electrically couple with the fluid medium and any cell in the flow passageway, e.g. such that the fluid medium and any cell in the flow passageway forms a dielectric for the first and second measurement capacitors. The operative surfaces of the first and second measurement capacitors may be exposed to the fluid medium, with no intermediate layer. The operative surfaces of the first and second measurement capacitors may conduct into the fluid medium.

[0091] The electrodes of the first and second measurement capacitors may take the form of an electrode array, which is formed on a surface of a semiconductor device. The apparatus may comprise a plurality of electrode arrays, i.e. a plurality of pairs of first and second measurement capacitors. The fabrication process for the electrode array may lack a polyimide layer deposition step, such that no polyimide top layer is present. The electrode array may have a passivation layer, e.g., a silicon nitride layer, but may be without any passivation layer over the electrodes, such that the electrodes conduct into the fluid medium. The hydrophilic nature of the passivation layer provides for maximum exposure, with the openings in the passivation layer between the electrodes and the fluid medium enabling conduction between the electrodes and the fluid medium. The size of the electrodes is selected depending on the size of the cells being measured.

[0092] The operative surfaces of the stimulus electrodes of the first and second measurement capacitors may be separated from each other, aligned transversely relative to the flow of fluid medium, e.g., with the first stimulus electrode being aligned with a flow of fluid medium only, i.e. without cells to be measured, and the second stimulus electrode may be aligned with a flow of fluid medium and cells to be measured.

[0093] The operative surfaces of the sensing electrodes of the first and second measurement capacitors may be separated from each other, aligned transversely relative to the flow of fluid medium, e.g., with the first stimulus electrode being aligned with a flow of fluid medium only, i.e. without cells to be measured, and the second stimulus electrode may be aligned with a flow of fluid medium and cells to be measured. The first and second electrodes are nevertheless electrically connected to each other, e.g., under an insulating layer, such as the passivation layer. The sensing electrodes may each be disposed adjacent to, but separated from, a corresponding stimulus electrode, thereby providing the first and second measurement capacitors. In each measurement capacitor, the stimulus electrode may be upstream or downstream of the sensing electrode, and the first and second measurement capacitors may have the same arrangement.

[0094] An electrode may have a dimension, such as at least one of width and height, of less than substantially 200 microns, 100 microns, 50 microns, 30 microns, 20 microns, 15 microns, 10 microns, 5 microns, 3 microns or 1 micron. Alternatively, or in addition, an electrode may have a dimension of more than substantially 0.5 microns, 1 micron, 5 microns, 10 microns, 15 microns, 20 microns, 30 microns or 50 microns.

[0095] The distance between the electrodes of the first measurement capacitor and the electrodes of the second measurement capacitor may be selected such that there is a sufficient separation of the respective electrical fields for a cell at one measurement capacitor to have a small or negligible impact on the response of the other measurement capacitor.

[0096] A second complementary net zero electrode arrangement may be provided, which may be disposed upstream or downstream of the net zero electrode arrangement described above. The electrodes of this complementary net zero electrode arrangement may have the same layout and circuitry as the electrodes of the first net zero electrode arrangement.

[0097] The same electric stimulus signal may be provided to the stimulus electrodes of each of the first and second net zero electrode arrangements, with the stimulus electrodes of the first measurement capacitor in each arrangement being electrically connected to each other and the stimulus electrodes of the second measurement capacitor in each arrangement being electrically connected to each other.

[0098] The output signals from the sensing circuit associated with the upstream and downstream net zero electrode arrangements may be compared, e.g. by subtraction, such that a differential measurement is made. In particular, the concentration of cells and the flow rate of the fluid medium may be controlled such that each cell in the fluid medium passes over one of the measurement capacitors of the first net zero electrode arrangement and then, subsequently, passes over one of the measurement capacitors of the second net zero electrode arrangement. The use of this differential arrangement enables any mismatch from sources affecting the measurement in each fluid stream to be removed. This mismatch may be in the rise and fall times of the stimulus, for example, or in the analyte, e.g., caused by the cells breathing and consequent changes to the fluid medium.

[0099] In one embodiment, the stimulus electrodes of the first measurement capacitor in each arrangement are combined, and provided by a single stimulus electrode, and the stimulus electrodes of the second measurement capacitor in each arrangement are combined and provided by a single stimulus electrode. In this embodiment, the stimulus electrode of the first measurement capacitors of the net zero electrode arrangements may be disposed between the sensing electrodes of the first measurement capacitors of the net zero electrode arrangements, and the stimulus electrode of the second measurement capacitors of the net zero electrode arrangements may be disposed between the sensing electrodes of the second measurement capacitors of the net zero electrode arrangements.

[0100] In this arrangement, the stimulus electrodes act as an isolator between the first and second net zero electrode arrangements. An alternative option for providing isolation between the first and second net zero electrode arrangements, e.g., where the first and second net zero electrode arrangements have separate stimulus electrodes, would be to provide an electrode between the sensing electrodes of the first and second net zero electrode arrangements, with this electrode being in contact with the fluid medium and being provided with a DC voltage, such that the electric fields of the first and second net zero electrode arrangements are isolated from each other. However, this alternative arrangement uses a DC voltage which may have electrochemical effects that are undesirable. The use of combined stimulus electrodes of the first and second net zero electrode arrangements to provide isolation overcomes these disadvantages.

[0101] Furthermore, the use of combined stimulus electrodes of the first and second net zero electrode arrangements enables the distance between the two sensing electrodes in each fluid medium stream to be reduced relative to an arrangement in which the first and second net zero electrode arrangements have separate stimulus electrodes. This increases the maximum cell concentration that may be used with the apparatus, as the apparatus is controlled such that one cell crosses over the entire electrode array before a second cell starts to cross the electrode array.

[0102] In a preferred method of the invention, the pre-determined, electrodynamic field comprises a pseudo-random noise signal. The measurement apparatus may be configured to generate the pseudo-random noise signal. The pseudo-random noise signal may be generated from a pseudo-random binary sequence. The pseudo-random binary sequences are generated with a deterministic algorithm. The pseudo-random binary sequence nevertheless exhibits statistical behaviour similar to a truly random sequence. The pseudo-random binary sequence may be a maximum length sequence, a so-called “m-sequence”, which may be generated by a linear feedback shift register. Where a binary sequence is generated by a linear feedback shift register, the output eventually repeats itself. An m-sequence is the longest possible non-repeating sequence for a given number of shift registers.

[0103] The pseudo-random noise signal may therefore comprise a m-sequence. M-sequences exhibit a flat power spectral density across a desired bandwidth of operation. Furthermore, m- sequences may be readily provided for by way of standard digital circuitry and thus may be suited to implementation in an integrated circuit formed by a semiconductor fabrication process, such as CMOS.

[0104] The stimulation circuit may be operative to generate a stimulation signal in the form of an m- sequence by way of a linear feedback shift register or otherwise as would be within the ordinary design skills of the person skilled in the art. For example, the stimulation circuit may comprise memory storing the m-sequences. Alternatively, an m-sequence may be provided by an external signal generator.

[0105] The length of each m-sequence is 2n- 1 , where n is the number of registers in the linear- feedback shift register. The range of frequencies provided by the pseudo-random binary sequence may be determined by the length of each of the pseudo-random binary sequence, determined in numbers of bits, and the bit rate of the electric stimulus signal.

[0106] The range of frequencies of the pseudo-random binary sequence is determined by the binary signal achievable with the length of the pseudo-random binary sequence and the bit rate of the electric stimulus signal. The highest frequency of the range of frequencies may be an alternating sequence of bits, immediately adjacent to each other, which will have a frequency of half of the bit rate. The lowest frequency may be a constant value across the entire length of the sequence, which will have a frequency of the bit rate divided by the length of the sequence.

[0107] The electric stimulus signal may comprise a plurality of different pseudo-random binary sequences, e.g., a plurality of different m-sequences, each pseudo-random binary sequence having a length and data rate that provide the pre-determined, electrodynamic field with a range of frequencies that is different to the range(s) of frequencies provided by the other pseudo-random binary sequence(s). A plurality of different pseudo-random binary sequences providing a pre-determined, electrodynamic field with a plurality of different ranges of frequencies enable a greater breadth of frequencies for a given sequence length and data rate compared to a single pseudo-random binary sequence, which has a breadth of frequencies that is linearly proportional to its length. The present invention therefore enables a greater bandwidth for the biological measurement apparatus relative to using a pseudo-random binary sequence with one range of frequencies. Furthermore, a low-frequency signal may provide information regarding cell surface features, and a high-frequency signal may provide information regarding intracellular features.

[0108] The electric stimulus signal and hence the pre-determined, electrodynamic field may comprise a signal packet including the plurality of different pseudo-random binary sequences, with at least one signal packet including the plurality of different pseudo-random binary sequences being applied to each cell to be measured.

[0109] The measurement apparatus may comprise processing apparatus, which may include the stimulation circuit and / or the sensing circuit. The processing apparatus and / or the sensing circuit may be configured to receive the electric response signal and to convert the electric response signal to digital form. The processing apparatus and / or the sensing circuit may therefore have an analogue input and a digital output, such that the output is a digital response signal.

[0110] The processing apparatus and / or the sensing circuit may therefore comprise an analogue-to- digital converter and whatever signal conditioning circuitry may be required, such as an amplifier and an anti-aliasing filter. The processing apparatus may be constituted by any suitable electronic apparatus, such as a separate analogue-to-digital converter circuit, a separate amplifier circuit and a separate filter circuit or a configurable integrated circuit, such as an FPGA, or a dedicated integrated circuit, such as an Application Specific Integrated Circuit (ASIC), comprising such circuits.

[0111] The same clock may be used for the generation of the electric stimulus signal and the sample rate of the processing apparatus. This ensures that the electric stimulus signal does not drift in time relative to the digital response signal. The sample rate of the processing apparatus may, however, be different to the bit rate of the electric stimulus signal, as discussed in more detail below. The sample rate of the processing apparatus and the bit rate of the electric stimulus signal may also be expressed in terms of the sample period of the processing apparatus and the bit period of the electric stimulus signal. Where the clock used for the generation of the electric stimulus signal and the clock used for sampling are different, the respective clocks are preferably derived from the same clock.

[0112] The digital response signal may be stored in memory. The processing apparatus and / or the sensing circuit may comprise a processor and may be operative to decode the received output signal, which may be m-sequence encoded data.

[0113] The impulse response may be calculated by application of a Hadamard transform, such as the Fast Hadamard transform. This provides for rapid calculation of the impulse response. The fast Hadamard transform is given by: where is the estimated output spectrum of the system under test, m is the sequence order, H is the Hadamard matrix, q is the measured m-sequence encoded response, and and are the encode and decode matrices for transforming m-sequence data into the correct order for use with the Hadamard matrix. In one form, and are equal to each other.

[0114] Alternatively, analysis apparatus may be configured to decode the received output signal, which may be m-sequence encoded data, for example by cross-correlation. The analysis apparatus may be constituted by any suitable electronic apparatus, e.g., a general-purpose computer, such as a Personal Computer (PC).

[0115] The analysis apparatus may be further operative to perform a Fourier Transform, such as a Fast Fourier Transform (FFT), on the decoded output signal to thereby provide frequency domain data. The frequency domain data may be displayed for user interpretation.

[0116] The response data derived from multiple frequencies of the stimulus signal for a particular cell, eg the frequency domain data for a particular cell, may provide a point or vector in multidimensional space for that particular cell. The use of m-sequences enables data to be obtained at many frequencies, and hence many dimensions, from each cell. Each cell measurement may therefore comprise a point or vector in multidimensional space. For ease of interpretation, data may be dimensionally reduced to be and displayed for user interpretation, e.g., as a 2-dimensional scatterplot. The comparison between the first and second output signals to determine a measure of differentiation between said first and second cell-type may comprise a comparison of a point or vector in multidimensional space for each cell. The comparison of cell populations relative to each other may include comparative statistic for high dimensional data, such as a modified Chi square or Hotelling’s statistics.

[0117] The apparatus may be calibrated before use. In particular, the system response of the apparatus may be measured and recorded before use of the apparatus, and the system response may be removed from the electric field sensed by the apparatus during processing of the sensed electric field data.

[0118] The apparatus may comprise a main instrument and a removable module, which may each include electronics, eg one or more microchips, of the sensing circuit. The apparatus system response may therefore comprise the response of the main instrument plus the response of the removable sensor module. The combination of these two components results in a system response that is unique to that particular component combination. This means that the system response for a given apparatus is different for each removable sensor module.

[0119] Traditional methods of calibration to correct for differences in system responses involve passing polystyrene beads through the instrument. Polystyrene beads are uniform and their response is consistent. This means that differences seen in the bead signature between instruments is due to the system response. An inverse filter can then be found, which will convert bead response to an impulse. In practice, this is numerically unstable and the filter is designed to shape the system response to a band-limited version of an impulse, such as a gaussian. Applying this filter to cell data will then remove the system response from the data and make data acquired on different instruments comparable. However, the use of beads in calibration is a time-consuming process, which must be done for each instrument plus removable module combination.

[0120] In a preferred embodiment of the invention, the system response is recorded using an electronic sense loop, which may be recorded before each use of the instrument is commenced. The electronic sense loop may comprise applying an input signal to the sensing circuit of the apparatus, eg of the main instrument and the removable module, and sensing the response of the sensing circuit to the input signal, thereby deriving the system response of the apparatus. Making a measurement of the system response every time the instrument is used means that any small changes in the system response between uses are captured, resulting in more accurate results. The system response calibration may therefore be run as an automatic process, eg before each use of the apparatus.

[0121] The measurement apparatus may be operative and also configured to be label free. The biological sensing apparatus therefore operates on fluent material lacking any label, such as a fluorochrome or microbeads.

[0122] The measurement apparatus may be operative and perhaps also configured for sensing of microbiological samples. The measurement apparatus may be configured for a cell size of cell or a range of sizes of cells in respect of a dimension of at least one of the stimulation apparatus and the sensing apparatus, such as a size of at least one electrode. More specifically, a dimension of at least one of the stimulation apparatus and the sensing apparatus may correspond to a size of cell or a range of sizes of cells.

[0123] The semiconductor fabrication process may be a planar semiconductor fabrication process. Alternatively, or in addition, the semiconductor fabrication process may be a metal-oxide semiconductor process, such as a CMOS process. Alternatively, or in addition, the semiconductor fabrication process may be a submicron semiconductor fabrication process, such as a 0.18 micron CMOS process and perhaps a high voltage 0.18 micron CMOS process.

[0124] The fluent material is cell culture medium appropriate to the first and / or second cell-types and known to the skilled artisan suitable for maintaining growth and proliferation of cells, e.g., mammalian cells, microbial cells, plant cells or insect cells. Cell culture medium typically contains A typical culture medium is composed of a complement of amino acids, vitamins, inorganic salts, carbohydrate e.g. glucose, growth factors and hormones to list but a few essential components. Examples include Dulbeccc-’s modified Eagle’s medium for the growth of mammalian cells. Others include serum free medium and chemically defined medium for the cultivation of certain cell types that are problematic to culture.

[0125] If microbial cells are used in in the process according to the invention, they are grown or cultured in the manner with which the skilled artisan is familiar, depending on the host microbial organism. As a rule, microbial cells are grown in a liquid medium comprising a carbon source, usually in the form of sugars, a nitrogen source, usually in the form of organic nitrogen sources such as yeast extract or salts such as ammonium sulfate, trace elements such as salts of iron, manganese and magnesium and, if appropriate, vitamins. The measurement apparatus may comprise, or be adapted to be operative with, a flow apparatus that provides for flow of the fluent material and the cells in a flow passageway. In use, a cell sample of fluent material is introduced into a flow apparatus with the flow apparatus being configured to contain and provide for flow of the fluent material through the flow passageway. The flow apparatus may, for example, define an open-ended fluid passageway which contains the fluent material and allows for flow such as when flow is created by way of a pump. Alternatively, or in addition, the flow apparatus may be configured to actuate flow of itself. More specifically the flow apparatus may be configured to draw the fluent material through the flow apparatus by way of capillary action.

[0126] The flow apparatus may define a main channel through which the fluent material flows when in use. The sensing apparatus may be disposed relative to the main channel so as to provide for sensing of cells present in the main channel. The sensing apparatus may be disposed on at least one of first and second opposite sides of a flow of fluent material. Thus, for example, components such as sensing electrodes of the sensing apparatus may be disposed on one side of the flow of fluent material. According to another example, components of the cell sensing apparatus may be disposed on both sides of the flow of fluent material.

[0127] The flow apparatus may comprise a sample inlet which is configured to receive a sample of fluent material, e.g., by way of injection, which is to be subject to measurement, the sample inlet being in fluid communication with the main channel. The flow apparatus may comprise a sample outlet at an opposite end of the flow apparatus from the sample inlet, the sample outlet being in fluid communication with the main channel. The sample outlet may provide for flow of fluent material from the main channel.

[0128] The flow apparatus may comprise at least one further inlet disposed laterally of the sample inlet. More specifically, the flow apparatus may comprise first and second further inlets with the first inlet disposed laterally on one side of the sample inlet and the second inlet disposed laterally on another opposite side of the sample inlet. The at least one further inlet may be in fluid communication with the main channel. The flow of sheath fluid may provide for registration of the cell comprising fluent material with the cell sensing apparatus and may also help preserve the integrity of the flow of fluent material as it progresses though the flow apparatus.

[0129] The flow apparatus may be formed from glass and / or at least in part from a polymer, such as poly(methyl methacrylate) (PMMA). The stimulation and sensing apparatus may be formed separately from the flow apparatus. The stimulation and sensing apparatus may be disposed relative to the flow apparatus by attaching the stimulation and sensing apparatus and the flow apparatus to each other. The stimulation and sensing apparatus and the flow apparatus may be adhered together, for example by appropriate chemical or physical bonding, or may be mechanically attached to each other, e.g., by way of a fastener apparatus comprising a silicone gasket layer, which may be releasable. Appropriate chemical or physical bonding may include plasma bonding.

[0130] The cell measurement apparatus may be configured to be operable as a flow cytometer. The measurement apparatus may further comprise control apparatus. The control apparatus may be constituted by any suitable electronic apparatus, such as a microprocessor or a configurable electronic circuit, such as a Field Programmable Gate Array (FPGA).

[0131] The measurement apparatus may comprise flow inducing apparatus, i.e., a pump, which is operative to induce a flow of fluent material through the flow apparatus. The flow inducing apparatus may be controlled, for example in respect of a rate of flow of fluent material through the flow apparatus, in dependence on an output from the sensing apparatus. The control apparatus may be operative to receive an output from the sensing apparatus and to provide an output to the flow inducing apparatus in dependence thereon.

[0132] The sensing apparatus as described elsewhere herein may be operative to provide for determination of a rate of flow of fluent material through the flow apparatus, the rate of flow being received by the control apparatus. Where the sensing apparatus comprises, plural spaced apart sensing electrodes with each sensing electrode being operative to sense cells, the rate of flow may be determined in dependence on the separation between the sensing electrodes being known and a time between sensing of a cell by different sensing electrodes.

[0133] Alternatively, or in addition, characterisation of at least one cell as described elsewhere herein may be compared with a predetermined criterion and the flow inducing apparatus may be controlled in dependence on the comparison. For example, characterisation of the at least one cell may comprise a level of confidence value which is compared with a predefined value. More specifically, if the level of confidence value is below the predefined value the flow inducing apparatus may be operative to reduce a rate of flow of the fluent material to thereby provide for improved characterisation.

[0134] The processing apparatus may provide an output signal, e.g., a digital output signal. The output signal may be stored in memory of the measurement apparatus. The measurement apparatus may comprise an output for sending the output signal to analysis apparatus, which may or may not be integrated with the measurement apparatus.

[0135] The analysis apparatus may be configured to make determinations with regards to cells comprised in the fluent material in dependence on at least one output from the cell sensing apparatus. For example, the analysis apparatus may be operative to make determinations in dependence on electric field measurements made by the cell sensing apparatus after analogue to digital conversion. Determinations may be made in respect of the like of the density of cells comprised in the fluent material, differentiation of one form of cell from another, for example in relation to expression of endogenous or recombinant expression and characteristics of cells such as in respect their expression of said endogenous or recombinant expression. The analysis apparatus may be constituted by any suitable electronic apparatus, e.g., a general-purpose computer, such as a Personal Computer (PC), an embedded microprocessor, a configurable electronic circuit, such as a FPGA or the like. Further embodiments of this aspect of the present invention may comprise one or more further features of the first aspect of the present invention.

[0136] The sensor chip may be configured to be mounted within a bioreactor, e.g., from microbioreactors to large bioreactors. Microbioreactors are particularly suitable for use in personalised medicine, e.g., small batches may be required on a per patient basis.

[0137] Throughout the description and claims of this specification, the words “comprise” and “contain” and variations of the words, for example “comprising” and “comprises”, means “including but not limited to”, and is not intended to (and does not) exclude other moieties, additives, components, integers or steps. “Consisting essentially” means having the essential integers but including integers which do not materially affect the function of the essential integers.

[0138] Throughout the description and claims of this specification, the singular encompasses the plural unless the context otherwise requires. In particular, where the indefinite article is used, the specification is to be understood as contemplating plurality as well as singularity, unless the context requires otherwise.

[0139] Features, integers, characteristics, compounds, chemical moieties or groups described in conjunction with a particular aspect, embodiment or example of the invention are to be understood to be applicable to any other aspect, embodiment or example described herein unless incompatible therewith. An embodiment of the invention will now be described by example only and with reference to the following figures:

[0140] Figure 1A. AuraCyt™ signatures, for 3 biologically distinct cell lines THP1 , CHO and Jurkat, presented as principle component analysis (PCA) on averaging 25 events;

[0141] Figure 1 B - Flow cytometry analysis to confirm THP-1 phenotype;

[0142] Figure 1 C - Flow cytometry analysis to confirm CHO phenotype;

[0143] Figure 1D - Flow cytometry analysis to confirm Jurkat phenotype;

[0144] Figure 1 E. High frequency response data generated using AuraCyt™ for THP-1 , CHO and Jurkat cells;

[0145] Figure 1F Normalized Mean Root Square Deviation (NMRSD) analysis of THP-1 and CHO cells AND THP-1 and Jurkat cells to determine variance throughout data collection, between technical replicates and between cell lines;

[0146] Figure 2 AuraCyt™ data presented as principle component analysis (PCA) for live (ovoid box bottom right, broken line) and apoptotic (ovoid box top left) THP-1 cells. Distinct separation is observed between populations of each cell status when comparing AuraCyt™ signatures;

[0147] Figure 3 - Flow Cytometry analysis of live cells THP-1 cells stained with known dyes for membrane integrity loss and apoptosis detection (Propidium Iodide and Annexin V respectively);

[0148] Figure 4 - Flow Cytometry analysis of THP-1 cells, subjected to induced apoptosis by Camptothecin treatment and stained with known dyes for membrane integrity loss and apoptosis detection (Propidium Iodide and Annexin V respectively);

[0149] Figure 5 - Identification of distinct AuraCyt™ signatures within complex cell mixes, attested by flow cytometry analysis; Figure 6 - Distinguishing cell types from one another using AuraCyt™ signatures with statistical significance by comparing a control signature (A549 cells) to 4 different cell types (Jurkat, Kellys, MDCK and THP-1 cells);

[0150] Figure 7 A- Longitudinal analysis of AuraCyt™ profiles showing that profiles of a known cell type (Jurkat) remain stable over time (no significant difference in profile from Day 0 to Day 20 in culture);

[0151] Figure 7B - Longitudinal analysis of AuraCyt™ profiles showing that profiles of a known cell type (THP-1) remain stable over time (no significant difference in profile from Day 0 to Day 20 in culture);

[0152] Figure 7C - Distinguishing cell types from one another using AuraCyt™ signatures with statistical significance by comparing a control signature (Jurkat) to 4 THP-1 cells over a 4-day period. This shows that AuraCyt™ signatures can be used to monitor cell growth throughout a culture period;

[0153] Figure 8 is a block diagram representation of biological measurement apparatus;

[0154] Figure 9 is a representation of a flow apparatus and an electrode array that is part of the biological measurement apparatus embodiment;

[0155] Figure 10 is a circuit representation of sensing apparatus that is part of the biological measurement apparatus embodiment;

[0156] Figure 11. AuraCyt™ data presented as principal component analysis (PCA) for Day 0 haematopoietic stem cells (elliptical gate A) prior to initiation of a macrophage differentiation protocol and HSC-derived macrophages on day 10 of the differentiation protocol (elliptical gate B). Significantly distinct AuraCyt™ signatures (p<0.05) were observed when comparing HSCs with HSC-derived macrophages indicating that AuraCyt™ can identify and monitor changes in cell phenotype during directed differentiation;

[0157] Figure 12A PCA of AuraCyt™ calibration bead data across six test days. Bead data were collected on two instruments and two modules and used to assess and compensate system performance via Maestro software. PCA before compensation shows consistent clustering; one outlier test (purple) was excluded due to temperature fluctuations. Compensation minimised instrument variability prior to cell data analysis. Figure 12B - PCA of AuraCyt™ calibration bead data after compensation, post-compensation bead data shows strong alignment of signal profiles across instruments and modules. These settings were applied to align cell data prior to gating, ensuring consistent performance for subsequent analysis.

[0158] Figure 13A - T-SNE of AuraCyt™ analysis of individual cell lines to generate unique signatures and gating regions. Jurkat (CD3, CD4), KG-1 (CD34), and THP-1 (CD14, CD32) cells were analysed individually to define distinct signatures. Following calibration, t-SNE was applied to reduce dimensionality and visualize population-specific profiles. Gating regions were generated based on these unique signatures for subsequent classification.

[0159] Figure 13B - Classification of a mixed cell population using predefined gates from individual cell line signatures. Jurkat (CD3, CD4), KG-1 (CD34), and THP-1 (CD14, CD32) cells were combined in a 1 :1 :1 ratio to model the heterogeneity of an apheresis product. The mixed sample was analysed using AuraCyt™, and cell populations aligned with gates established from individual cell line profiles. The t-SNE plot shows clear separation into three distinct regions, confirming accurate classification and even distribution of each cell type.

[0160] Figure 14A - PCA of AuraCyt™ signatures differentiates productive, non-productive, and control conditions in lentiviral vector production. Three conditions were assessed: (1) cells transfected with a high-titre transfer plasmid containing the gene of interest (productive capsids), (2) cells transfected without the transfer plasmid to produce virus-like particles (nonproductive capsids), and (3) untransfected control cells. Samples were collected at 0, 24, and 48 hours post-transfection and analysed in triplicate using the Celledonia device. PCA of AuraCyt™ signatures revealed statistically significant differences (P < 0.05) between all three conditions at 24 and 48 hours, demonstrating AuraCyt™’s ability to assess capsid productivity in real time.

[0161] Figure 14B - Figure 14B. Effect size analysis of AuraCyt™ signatures over time to assess lentiviral vector production. Cohen’s d was used to calculate effect size at 24 and 48 hours relative to the 0-hour baseline for each condition: productive capsid, non-productive capsid, and untransfected control. AuraCyt™ signatures showed minimal change in control cells (P > 0.05), while both productive and non-productive conditions exhibited increasing effect sizes over time, consistent with viral particle production. Notably, the productive capsid condition was significantly different (P < 0.05) from both control and non-productive groups, demonstrating AuraCyt’s potential to detect and monitor productivity early in the manufacturing process.

[0162] Figure 15A - PCA of AuraCyt™ signatures distinguishes HEK293 cell lines with differing exosome release profiles. Wild-type HEK293T cells (HEK293T) and a proprietary low exosome-releasing variant (LowExo) were cultured under identical conditions and analysed over three consecutive days (D1-D3) post-passage. Cell samples were run in triplicate on the Celledonia™ instrument, and AuraCyt™ signatures were generated following calibration. PCA scatterplots revealed significant shifts (P<0.05) between the two cell lines at each timepoint, demonstrating AuraCyt™’s ability to differentiate exosome release profiles.

[0163] Figure 15B- Effect size analysis of AuraCyt™ signatures reveals increasing differences between high and low exosome-releasing HEK293T cell lines. AuraCyt™ signatures from LowExo cells were compared to HEK293T cells across three post-passage timepoints (D1- D3), and effect size was calculated using Cohen’s d to assess the magnitude of population differences. A significant shift (P < 0.05) was observed between the two lines on all test days, with effect size increasing over time. These results align with known trends of elevated exosome release in HEK293T cells as culture duration increases, demonstrating AuraCyt™’s ability to sensitively detect biologically relevant changes in cell populations.

[0164] Figure 16A - PCA of AuraCyt™ signatures detects lentiviral production dynamics in HEK293T cells. A high-producing HEK293T cell line was analyzed under two conditions: (1) untransfected control and (2) LVV-GFP-transfected test group. Cells were cultured under standard conditions, and samples were collected at 24 and 48 hours post-transfection. PCA scatterplots of AuraCyt™ signatures, generated using the Celledonia™ instrument, revealed significant shifts (P < 0.05) between transfected and control conditions. These changes intensified over time, reflecting increased lentiviral production consistent with expected manufacturing kinetics.

[0165] Figure 16B - PCA of AuraCyt™ signatures detects early lentiviral production changes in LowExo HEK293T cells. A LowExo HEK293T cell line was evaluated under two conditions: (1) untransfected control and (2) LW-GFP-transfected test group. Cells were cultured under standard conditions, with samples collected at 24 and 48 hours post-transfection. PCA scatterplots of AuraCyt™ signatures, generated via the Celledonia™ instrument, showed significant shifts (P < 0.05) between control and transfected cells as early as 24 hours, with changes intensifying by 48 hours. These results align with expected kinetics of lentiviral production, confirming AuraCyt’s ability to detect early productivity signals in low exosome- releasing cell lines.

[0166] Figure 16C - Effect size analysis of AuraCyt™ signatures differentiates lentiviral productivity between HEK293T and LowExo cell lines. To assess productivity, HEK293T and LowExo cells were transfected with LW-GFP and compared to untransfected controls at 24 and 48 hours post-transfection. Effect size was calculated to quantify the magnitude of difference between transfected and control conditions for each cell line. At 48 hours, transfected HEK293T cells showed an AuraCyt™ effect size 2.3 times greater than that of transfected LowExo cells, aligning with the developer’s observation that HEK293T cells produce 2-2.5 times more lentivirus. These results demonstrate AuraCyt’s ability to quantitatively monitor productivity differences across manufacturing cell lines.

[0167] MATERIALS AND METHODS

[0168] Detailed Description of Device

[0169] A block diagram representation of biological measurement apparatus 10 according to the present invention is shown in Figure 8. The biological measurement apparatus 10 comprises flow apparatus 30, stimulation apparatus 12, sensing apparatus 13, control and processing apparatus 14, and analysis apparatus 16. The stimulation apparatus 12 and sensing apparatus 13 receive, via the flow apparatus 30, a flow of analyte in which biological cells are suspended.

[0170] The flow of analyte 18 is directed by the flow apparatus 30 to the stimulation apparatus 12 and sensing apparatus 13 where it is subject to stimulation and sensing, as described in detail below, before exiting 20 from the biological measurement apparatus 10. Although not shown in Figure 8, the flow apparatus 30 further comprises a pump which is operative to push or draw analyte to the stimulation apparatus 12 and sensing apparatus 13, via the flow apparatus 30.

[0171] The control and processing apparatus 14 controls the application of stimulation signals to the analyte by the stimulation apparatus 12, and processes signals sensed by the sensing apparatus 13. Processing comprises amplification of sensed signals, analogue to digital conversion of sensed signals and storage of converted sensed signals. The analysis apparatus 16 is operative for analytical determination in dependence on the stored converted sensed signals.

[0172] The control and processing apparatus 14 is constituted by a System-on-a-Chip (SOC) comprising the digital circuits and a CMOS ASIC comprising the analogue circuits. The analysis apparatus 16 is constituted by any suitable electronic apparatus, e.g. a general purpose computer, such as a PC, an embedded microprocessor, a configurable electronic circuit, such as an FPGA, or the like. The control and processing apparatus 14 and analysis apparatus 16 are constituted apart from each other, e.g. as separate modules, or constituted together, e.g. in a same integrated circuit.

[0173] With reference to Figure 9, the biological measurement apparatus 10 comprises a two- dimensional array of electrodes 32, which comprise stimulation electrodes (102a, 102b) of the stimulation apparatus 12 and sensing electrodes (202a, 202b, 204a, 204b) of the sensing apparatus 13. The flow apparatus 30 and the array of electrodes 32 are disposed in relation to each other such that the array of electrodes 32 is exposed to first and second channels 31 a, 31b of the flow apparatus 30.

[0174] The control and processing apparatus 14 is electrically coupled to the array of electrodes 32. The control and processing apparatus 14 is operative to provide for biological cell stimulation and sensing by way of the array of electrodes 32.

[0175] The array of electrodes 32 are constituted by a CMOS process such as a 0.18 micron CMOS process. The array of electrodes 32 and the control and processing apparatus 14 are both comprised in a CMOS ASIC.

[0176] The thickness and permittivity of the standard polyimide top layer of the ASIC provides insufficient capacitance for proper engagement of the electrodes 32 with the analyte, and hence the fabrication process lacks a polyimide layer deposition step so no polyimide top layer is present. The hydrophilic nature of the silicon nitride layer provides for maximum exposure. However, the silicon nitride layer is removed over the electrodes, such that the electrodes conduct into the analyte. The ASIC is disposed, as is mentioned above, relative to the flow apparatus 30 such that the array of electrodes 32 is exposed to the analyte flowing through the flow apparatus 30.

[0177] The surfaces of the electrodes that contact the analyte may be treated to protect them from corrosion, for example with noble-metal deposition or metal removal. In one embodiment, a CMOS chip comprising aluminium electrodes is treated to remove the aluminium electrodes and expose the tungsten vias that connect metal layers within the chip and extend through dielectric layers. The exposed tungsten vias, which were previously under each aluminium electrode, thereby form an array of discrete conductive elements, Each array of tungsten vias, corresponding to a removed aluminium electrode, constitutes an electrode of the electrode array 32.

[0178] The flow apparatus 30 has a length of about 25mm and a width of about 10mm. The flow apparatus 30 comprises first and second channels 31 a, 31b through which the analyte flows across the array of electrodes 32. The array of electrodes 32 is disposed above the first and second channels 31 a, 31b so that the electrodes engage with the analyte as the analyte flows through the first and second channels 31 a, 31 b.

[0179] As is described above, the array of electrodes 32 is comprised in a CMOS ASIC. The CMOS ASIC and the flow apparatus 30 are bonded to each other, such that a proper relative disposition of electrodes and main channel is achieved. In particular, the array of electrodes 32 is disposed on a generally planar operative surface of the CMOS ASIC, and the flow apparatus 30 is formed of a polymeric or glass component that is fastened or bonded to the CMOS ASIC, such that the first and second channels 31 a, 31 b are defined between the flow apparatus 30 and the operative surface of the CMOS ASIC.

[0180] The flow apparatus 30 also comprises a sample inlet 40 which receives the analyte, e.g. by way of injection, and a sample outlet 50 at an opposite end of the flow apparatus from the sample inlet 40. The sample inlet 40 and the sample outlet 50 are each in fluid communication with the first and second channels 31 a, 31 b.

[0181] Stimulation and sensing comprises electric field stimulation and electric field sensing. A biological cell cooperates with the applied electric field whereby the electric field is disturbed. Different sizes of a particular type of biological cell will disturb an applied electric field in a different manner. In addition, different types of biological cell will disturb an applied electric field in a different manner. Sensing of the electric field in dependence on the disturbance can therefore provide for detection of the presence of biological cells, determination of relative sizes of cells and differentiation of different types of cell from each or one another.

[0182] The first and second channels 31 a, 31 b of the flow apparatus 30 each has a width that is sufficient for the array of electrodes 32 to be disposed within the flow of analyte 34, with the cells being focussed into a cell and fluid medium stream 34a that flows over electrodes 102a, 202a and 204a, and a fluid medium stream 34b (with no cells) that flows over electrodes 102b, 202b and 204b.

[0183] The size of the electrodes is selected depending on the size of the cells being measured. In the electrode array 32 of Figure 9, electrodes 102a and 102b are a pair of stimulus electrodes, which are each provided with an electric stimulus signal, as discussed in more detail below with reference to Figure 10. The pair of stimulus electrodes 102a and 102b are separated from each other, aligned transversely relative to the flow of analyte, with a first stimulus electrode 102a being aligned with the cell and fluid medium stream 34a and the second stimulus electrode 102b being aligned with the fluid medium stream 34b.

[0184] Electrodes 202a and 202b are a first pair of sensing electrodes. The surfaces of the sensing electrodes 202a and 202b that are exposed to the analyte are separated from each other, aligned transversely relative to the flow of analyte, with a first sensing electrode 202a being aligned with the cell and fluid medium stream 34a and the second sensing electrode 202b being aligned with the fluid medium stream 34b. Although surfaces of the sensing electrodes 202a and 202b that are exposed to the analyte are separated from each other, the sensing electrodes 202a and 202b are electrically connected to each other under the silicon nitride layer.

[0185] The sensing electrodes 202a, 202b are each disposed adjacent to, but separated from, a respective stimulus electrode 102a, 102b, thereby providing two stimulus-sensing pairs of electrodes - a stimulus-sensing pair of electrodes 102a and 202a aligned with the cell and fluid medium stream 34a, and a stimulus-sensing pair of electrodes 102b and 202b aligned with the fluid medium stream 34b. In each stimulus-sensing pair of electrodes, 102a, 202a and 102b, 202b, the stimulus electrode 102a, 102b is downstream from the sensing electrode 202a, 202b.

[0186] Each stimulus-sensing pair of electrodes, 102a, 202a and 102b, 202b, forms two plates of a capacitor, with the fluid medium and any cell forming a dielectric between those plates. In this embodiment, the stimulus electrodes 102a, 102b and the sensing electrodes 202a, 202b each have a size of 20 pm x 20 pm. The separation between the stimulus electrode 102a, 102b and the sensing electrode 202a, 202b in each stimulus-sensing pair is 4 pm, and the separation between the stimulus and sensing electrodes 102a, 202a aligned with the cell and fluid medium stream 34a, and the stimulus and sensing electrodes 102b, 202b aligned with the fluid medium stream 34b, is 100 pm.

[0187] With reference to Figure 10, the electric stimulus signals provided to stimulus electrodes 102a and 102b via input 118 are identical but have an opposite polarity. The electric response signal is received from a connection 250 equidistant from each of the sensing electrodes 202a, 202b.

[0188] When no cell is present in the cell and fluid medium stream 34a, both stimulus-sensing pairs of electrodes, 102a, 202a and 102b, 202b, will have the fluid medium, but no cell, as a dielectric. As the electric stimulus signals provided to stimulus electrodes 102a and 102b via input 118 are identical, but have an opposite polarity, and the dielectric between each stimulus-sensing pair of electrodes, 102a, 202a and 102b, 202b, is the same (both fluid medium only), the response signals provided by the sensing electrodes 202a, 202b will cancel each other out and a net zero output will be obtained from the connection 250 equidistant from each of the sensing electrodes 202a, 202b.

[0189] When a cell is located adjacent to the stimulus-sensing pair of electrodes 102a and 202a aligned with the cell and fluid medium stream 34a, this stimulus-sensing pair of electrodes 102a and 202a will have both a cell and the fluid medium as a dielectric, whereas the other stimulus-sensing pair of electrodes 102b and 202b will have the fluid medium, but no cell, as a dielectric. The presence of the cell will cause the response signals provided by the sensing electrodes 202a, 202b to be different, such that the difference caused by the cell will be obtained as at output, relative to zero, from the connection 250 equidistant from each of the sensing electrodes 202a, 202b

[0190] The output from the connection 250 equidistant from each of the sensing electrodes 202a, 202b is compared to a common mode voltage, and the difference is output 230 as the electric response signal.

[0191] Previous attempts at providing an electrode array for a net zero measurement have used a single sense electrode that is disposed between two stimulus electrodes. However, the inventors found that this electrode arrangement is very sensitive to the position of the cell relative to the sensing electrodes. In particular, the optimal position for the cell in that arrangement is equidistant from one of the stimulus electrodes and the sensing electrode, and also close to the surface of those electrodes. However, the electric response signal reduces dramatically in strength as the position of the cell moves away from this optimal position. For example, the electric response signal is zero when the cell is over the sensing electrode, and hence equidistant from the two stimulus electrodes.

[0192] The inventors have found that providing a sense electrode that is split, or separated, in the flow channel, but is electrically connected under an insulating layer, provides the same net zero arrangement as a single sensing electrode arrangement, but separates the electric fields generated by the two stimulation electrodes, such that the electric response signal is less sensitive to the position of the cell relative to the sensing electrodes.

[0193] In the electrode array 32 of Figure 9, a complementary, downstream net zero electrode arrangement is provided by sensing electrodes 204a, 204b, disposed downstream of the upstream net zero electrode arrangement provided by electrodes 102a, 102b, 202a and 202b described above. The sensing electrodes 204a, 204b of this complementary, downstream net zero electrode arrangement have the same layout and circuitry as the sensing electrodes 202a, 202b of the upstream net zero electrode arrangement, with the only difference being that the sensing electrodes 204a, 204b of the downstream net zero electrode arrangement are disposed downstream of the stimulation electrodes 104a, 104b.

[0194] In particular, the first stimulus electrode 102a is disposed between the sensing electrodes 202a, 204a that are aligned with the cell and fluid medium stream 34a, and the second stimulus electrode 102b is disposed between the sensing electrodes 202b, 204b that are aligned with the fluid medium stream 34b.

[0195] The output signals from the sensing circuit associated with the upstream and downstream net zero electrode arrangements are compared, e.g. by subtraction, such that a differential measurement is made. In particular, the concentration of cells and the flow rate is controlled such that each cell in the flow passes over the first pair of electrodes 102a, 202a and then the second pair of electrodes 102a, 204a. The differential measurement will be zero until a cell passes over the first pair of electrodes 102a, 202a or the second pair of electrodes 102a, 204a, when a differential signal will be output.

[0196] The use of this differential arrangement enables any mismatch from sources affecting the measurement in each fluid stream 34a, 34b to be removed. This mismatch may be in the rise and fall times of the stimulus, for example, or in the analyte, eg caused by the cells breathing and consequent changes to the fluid medium.

[0197] The stimulus electrodes 102a, 102b have a length in the direction of flow that is selected to be sufficient that the respective electrical fields are separated, such that a cell isn’t detected by both pairs of electrodes in the same fluid stream at the same time. In this embodiment, the stimulus electrodes 102a, 102b each have a size of 20 pm x 40 pm.

[0198] The stimulus electrodes 102a, 102b therefore act as an isolator between the first and second net zero electrode arrangements. Furthermore, the use of combined stimulus electrodes 102a, 102b enables the distance between the two sensing electrodes in each fluid medium stream 34a, 34b, namely the distance between sensing electrodes 202a and 204a and the distance between sensing electrodes 202b and 204b to be reduced relative to an arrangement having two pairs of stimulus electrodes. This increases the maximum cell concentration that may be used with the apparatus, as the apparatus is controlled such that one cell crosses over the entire electrode array before a second cell starts to cross the electrode array.

[0199] The pump of the flow apparatus 30 of Figure 1 is controlled in dependence on at least one of: a rate of flow of analyte through the flow apparatus 30; and a level of confidence of characterisation of the analyte flowing through flow apparatus 30. Considering rate of flow of analyte further, the separation between pairs of electrodes in the array is known and the time of travel of biological cells between pairs of electrodes is determined by the control and processing apparatus 14.

[0200] The control and processing apparatus 14 is then operative to determine the speed of movement of biological cells through the measurement apparatus 10. The control and processing apparatus 14 is then operative to control the pump in dependence on the determined speed. For example, if the determined speed is below a predetermined value the control and processing apparatus 14 is operative to increase the flow rate by controlling the pump. Considering level of confidence of characterisation of the analyte further, the control and processing apparatus 14 is operative to characterise biological cells and to determine a level of confidence of the characterisation. The control and processing apparatus 14 is further operative to compare the determined level of confidence with a predetermined level and then to control the pump in dependence thereon. If the determined level of confidence is below the predetermined level the control and processing apparatus 14 is operative to reduce the rate of flow by controlling the pump to thereby provide for improved characterisation of the biological cells.

[0201] The control and processing apparatus 14 of the ASIC comprises binary to decimal decoders and memory for row and column addressing of the array of electrodes 32, global configuration logic and bias circuitry for the sensor output signal paths. The global configuration logic is operative to provide for the like of memory resetting and the gating of control signals with respect to a global reset signal to ensure all control lines power up in a known state.

[0202] The measurement apparatus 10 further comprises a Printed Circuit Board (PCB) which supports and provides for electrical connectivity for electrical circuits which support the ASIC. The electrical circuits comprised in the PCB includes a SOC which is configured to provide various digital functions including the generation of stimulus signals, addressing of individual electrodes in the array of electrodes 32 and communication with a Universal Serial Bus (USB) module.

[0203] The SOC is operative to generate a stimulation signal in the form of an m-sequence that is stored in memory and output one bit at a time. In particular, in this embodiment, the stimulation signal consists of a higher frequency m-sequence, which is generated from a linear feedback shift register having 5 registers, and a lower frequency m-sequence, which is generated from a linear feedback shift register having 7 registers. The higher frequency m-sequence therefore has a length of 31 bits and the lower frequency m-sequence has a length of 127 bits. The bit rate of the higher frequency m-sequence of the stimulation signal is 950Mbps, and the bit rate of the lower frequency m-sequence of the stimulation signal is 50Mbps.

[0204] The PCB also includes input signal conditioning circuitry which is configured to receive stimulus signals from the SOC or from the external (un-illustrated) signal generator, and provide for programmable gain amplification of the voltage swing of the stimulus signals.

[0205] In addition, the PCB includes output signal conditioning circuitry which performs a variety of functions including fixed gain, low distortion amplification of sensed single ended signals followed by programmable gain amplification or attenuation of such initially amplified signals under the control of a PC.

[0206] The output signal conditioning circuitry also includes an analogue-to-digital converter. The sample rate of the analogue-to-digital converter is 200MHz. The analogue-to-digital converter is configured to sample the higher frequency m-sequence of the stimulation signal in four interleaved passes, providing a sample length of 124 bits. The theoretical bandwidth of this m-Sequence measurement is therefore 1 ,9GHz - 30.65MHz. Due to the x4 oversample ratio, the flat region of this bandwidth only extends to 475MHz, 1 / 4 of the theoretical bandwidth, but that through post processing, the higher frequency regions above this point are also accessible.

[0207] The analogue-to-digital converter is configured to sample the lower frequency m-sequence of the stimulation signal at 200MHz, which is four times greater than the bit rate of the lower frequency m-sequence of the stimulation signal. However, the analogue-to-digital converter is configured to discard samples that align with a transition point of the m-sequence, and to average the remaining 3 samples to provide the digital output.

[0208] Because the stimulus for both high and low frequency sections of the stimulus signal are from the same source, the low frequency stimulus signal must align to the sampling method. In this case, each low frequency sample period (20ns) is made up of 4 analogue-to-digital converter samples (5ns each), as well as 19 high frequency stimulus samples (~1.052ns each); 19*1.052ns = 20ns.

[0209] To stop significant contamination from one stimulus pattern to the next, a gap of at least one m-sequence period is maintained between the two sections of the capture.

[0210] In this specific implementation, the entire stimulus package, which includes both the high and low frequency signals, are stored in a single section of memory. This is then streamed out, bit by bit, at the high frequency data rate (950MHz in this example). The low frequency signal is created by padding out the (in this case 7-bit) M-Sequence signal by a factor of 19, so each bit lasts for 19 high frequency periods.

[0211] As described above, the PCB comprises a USB module. The USB module provides for communication with a PC running software operative to perform the functions of the analysis apparatus 16 of Figure 8. More specifically, the PC is operative to configure the ASIC 42 and the circuits comprised in the PCB. In addition, the PC receives real-time sensed data or blocks of data which have been acquired and stored locally from the SOC.

[0212] In a further embodiment, the apparatus consists of a main instrument and a removable module. The electrical field e(t) sensed by the apparatus is the result of a convolution between the stimulus waveform M(t), which is an m-sequence, the system response of the instrument S(t) and the impulse response of the target object G(t) (eg cell) plus added noise N(t): e(t) = M(t) * S(mk, ik, t) * G(t) + N(t) where * denotes convolution, irik denotes sensor module number k, and ik denotes instrument number k. The apparatus processes the sensed electrical field data to minimise N(t) and remove M(t) and S(t) in order to recover G(t), which is the response of the target independent of the instrument on which it was measured.

[0213] In this embodiment, the instrument system response S(t) consists of the response of the main instrument (ik) plus the response of a removable sensor module (mk). The combination of these two components results in a system response that is unique to that particular component combination. This means that the system response for a given instrument is different for each removable sensor module.

[0214] The apparatus is therefore configured to record the system response using an electronic sense loop, which is recorded before each use of the instrument is commenced, thereby providing calibration before each use. Making a measurement of the system response every time the instrument is used means that any small changes in the system response between uses are captured, resulting in more accurate results. The system response calibration is run as an automatic process without the need for bead measurements.

[0215] Cell line discrimination using AuraCyt™ signatures

[0216] Cytomos obtained cultures of authenticated Jurkat, THP-1 and Freestyle CHO-S cells from established cell banks. Cells were cultured in accordance with manufacturer’s instructions to produce cells banks for experimentation at 37°C and 5%CO2. These cells were further characterised using flow cytometry to detect known cell surface markers for each line confirming their specific cell identification. Cell lines, media components and flow cytometry markers are described below. THP-1 - THP-1 is a monocyte isolated from peripheral blood from an acute monocytic leukemia patient.

[0217] Complete Medium - RPMI-1640 Medium ( Merck Life Science UK, Cat. No. R0883-500ML), 10% Fetal Bovine Serum (Merk Life Scientific UK, Cat No. F7524-500ML), 2mM L-glutamine (Fisher Scientific, Cat No. 10453332).

[0218] Flow cytometry markers - PerCP / Cyanine5.5 anti-human CD32 (Biolegend 303216); Helix Blue viability dye (Bioloegend 425305); Alexa Flour 647 anti-human CD4 (Biolegend 300523)

[0219] Freestyle CHO-S - FreeStyleTM CHO-STM Cells are derived from the CHO cell line and are adapted to suspension culture in FreeStyleTM CHO Expression Medium. The CHO cell line was initiated from a biopsy of an ovary of an adult, female Chinese hamster in 1957. Repeated subculture with adaption to suspension by media manipulation as well as genetic manipulation (which would be radiation or chemical) lead to continuous status.

[0220] Complete Medium - 90% Freestyle™ CHO™ Expression Medium ( Life Technologies, Cat. No. 12651014), 8 mM L-Glutamine (Fisher Scientific, Cat. No. 10453332)

[0221] Flow cytometry markers - Integrin beta 5 Antibody (11-0497-42 Thermo Fisher); Helix NP™ Blue (Viability Dye) (425305 Biolegend).

[0222] Jurkats - Jurkat, Clone E6-1 is a clone of the Jurkat-FHCRC cell line, a derivative of the Jurkat cell line, which was established from the peripheral blood of a 14-year-old, male, acute T-cell leukemia patient.

[0223] Complete Medium - RPMI-1640 Medium ( Merck Life Science UK, Cat. No. R0883-500ML), 10% Fetal Bovine Serum (Merk Life Scientific UK, Cat No. F7524-500ML), 8mM L-glutamine (Fisher Scientific, Cat No. 10453332).

[0224] Flow cytometry markers -Alexa Fluor® 647 anti-human CD4 (300523 Biolegend); CD3 Monoclonal Antibody (OKT3), FITC (11-0037-41 eBioscience); Helix NP™ Blue (Viability Dye) (425305 Biolegend).

[0225] MDCK (Madin-Darby canine kidney) - Derived from the kidney of a normal female adult Cocker Spaniel in 1958.

[0226] Complete Medium - The base medium for this cell line is ATCC-formulated Eagle's Minimum Essential Medium (ATCC 30-2003). To make the complete growth medium, add the following components to the base medium: fetal bovine serum (ATCC 30-2020) to a final concentration of 10%. Kelly cells - human

[0227] Complete Medium - RPMI-1640 Medium (Merck Life Science UK, Cat. No. R0883-500ML), 10% Fetal Bovine Serum (Merk Life Scientific UK, Cat No. F7524-500ML), 2mM L-glutamine (Fisher Scientific, Cat No. 10453332).

[0228] Cell health status assessment using AuraCyt™ signatures

[0229] Cytomos obtained cultures of authenticated THP-1 cells which were cultured and used to assay for levels on apoptosis using flow cytometry and AuraCyt™ technology. Flow cytometry markers included propidium iodide to detect a loss of cell membrane integrity and Annexin V used to detect apoptosis.

[0230] To prepare cells for testing on Celledonia™, cells were induced to enter a state of cellular apoptosis by treating them with Camptothecin and incubating for 18 hours before they were assayed.

[0231] Apoptotic, necrotic and live cells were assayed using flow cytometry and AuraCyt™ technology on Celledonia™. To prepare cells for testing on Celledonia™, cells were taken from the culture environment and tested on the Celledonia ™ instrument directly in their respective growth media or PBS then assessed using AuraCyt™ technology.

[0232] Culture reagents

[0233] Discrimination of complex cell mixes using AuraCyt™ technology

[0234] Human peripheral blood mononuclear cells (PBMCs) were supplied (isolated by negative positive / negative selection using magnetic activated cell sorting (MACS)) on ice in 10ml PEA buffer (PBS with EDTA and albumin (2%), prepared by cell supplier) at a concentration of 1x107 / ml in 10ml, with a positive viability of approximately 98%. Prior to arrival, samples were stored in Transfix stabilisation buffer diluted 2:1 (Transfix: sample). To prepare the cells before testing by AuraCyt™ technology, 2.5x106cells were twice washed with buffer (14g Sucrose, 8.25g L-Serine in 500 mL de-ionised water). 150ul of sample was then transferred to Celledonia™ (Flute 1) for testing. Cell samples were tested concurrently by flow cytometry for known markers of blood lineages including Erythroid, Neutrophils, Monocytes, NK Cells, CD4 T Cells, CD8 T Cells and B cells. Unstained cells were also reported. Flow cytometry was performed independently by the cell supplier. FCS files from AuraCyt™ was assessed using third party FCS compatible software, FCSExpress, a typical flow cytometry analysis platform. Dimensionally reduced AuraCyt™ datasets, using the UMAP algorithm, generated scatterplots enabling the gating of distinct cell populations, reported as a percentage, within a heterogenous cell mixture. The spectral signature of each gated population was generated using the FCS spectral plotting function on data from the dimensionally reduced AuraCyt™ datasets.

[0235] Distinguishing cell types from one another using AuraCyt™ Technology

[0236] Cytomos obtained cultures of authenticated Jurkat, THP-1 , A549, Kelly and MDCK cells. Cells were cultured in accordance with manufacturer’s instructions to produce cells banks. AuraCyt™ signatures were generated for each line by preparation a single cell suspension (where adherent cultures were disaggregated prior to analysis) in low ionic buffer at 2.5 x 106 / mL prior to testing on Celledonia™ (Flute 1). Each cell line was prepared and tested on the day of optimal passage. Returned AuraCyt™ signatures were compared to one another using a comparative algorithm that has been modified (chi square) to assess high dimensional data to show significant differences or similarities between cell populations of different or same lineages. Both adherent and suspension cells were tested, and cell line specifics are described below. A549 cells were used as the control line against which all other cell lines were compared. Significant differences were reported with a T statistic (described below).

[0237] Jurkat - suspension cell line, human T cells, leukemia

[0238] THP1 - suspension cell line, human monocytes, leukemia

[0239] A549 - adherent cells, human epithelial, lung cancer

[0240] Kelly - adherent cells, human neuronal, neuroblastoma

[0241] MDCK - adherent cells, dog kidney, healthy

[0242] Cell culture monitoring Longitudinal analysis of cell cultures using AuraCyt™ signatures

[0243] Cytomos obtained cultures of authenticated Jurkat, and THP-1 cells. Cells were cultured in accordance with manufacturer’s instructions. AuraCyt™ signatures were generated for each line by preparation in low ionic buffer at 2.5 x 106 / mL prior to testing on Celledonia™ (Flute 1). Each cell line was prepared and tested on the day of optimal passage, where passaging occurred every 3 to 4 days, and signatures were generated every passage day over the duration of a 20-day culture.

[0244] Returned AuraCyt™ signatures were compared to one another using a modified algorithm (chi square) to assess high dimensional data to show significant differences or similarities between cell populations of different or same lineages. Comparisons included; 1. Jurkats at day one as the control (DO) against which all other Jurkats test days (up to day 20) were compared. 2. THP-1s at day one as the control (DO) against which all other THP-1 test days (up to day 20) were compared. 3. Jurkats at day 0 as the control against which all other test days (day 0 to day 4) were compared for both Jurkats and THP-1 cells.

[0245] Analysis using AuraCyt™ technology.

[0246] Analysis of signals detected by the sensor were processed using algorithms to create unique "fingerprints”. As multiple frequencies are used to characterise each cell, a ‘point’ in multidimensional space is generated per cell. For ease of interpretation, data are dimensionally reduced and displayed as a 2-dimensional scatterplot (PCA / UMAP). Depending on technology status, a comparative statistic was used to compare cell populations against one another. Either a modified Chi square or Hotelling’s statistics was used to assess high dimensional data. When using the modified Chi square, a Tx value was used to denote significance. The T(X) value provides an indication of the probability that two distributions are different. The higher the value of T(X), the greater the difference between the test and control sample, with a value of greater than 60 denoting a significant difference to the control. The lower T(X) the more similar the sample is to the control.

[0247] The Hotelling T squared test is a multivariate statistical test that enables the statistical significance of information rich high dimensional data to be determined. This statistic also provides statistical relevance to the compared cell populations to demonstrate how statistically similar or different they are where p<0.05 indicates significant difference. The multivariate Hotelling T2 test was supported by calculating the effect size with confidence intervals between and within groups as well as variance using Normalised Mean Root Square Difference (NMRSD) analysis.

[0248] The use of NMRSD to investigate variance was used to assess variance from the start to end of data collection to ensure that consistent cell captures were generated throughout the experiment. Variance was also calculated to investigate consistent capture of data from technical replicates (3 technical replicates per cell sample was generated as standard). Variance was also investigated when comparing cell lines to determine cell signature differences of biologically different starting materials.

[0249] AuraCyt™ frequency responses can be assessed independently in terms of both low and high frequency ranges to provide information regarding cell surface features and intracellular complexity respectively.

[0250] Monitoring cellular differentiation using AuraCyt™ (dielectric) signatures

[0251] Hematopoietic stem cells (HSC) were isolated from human donor apheresis product and expanded in growth media containing recombinant human stem cell factor, recombinant human FMS-like tyrosine kinase 3 ligand, recombinant human thrombopoietin and recombinant interleukin 3. HSCs were tested to confirm expression of a CD34+ phenotype (by flow cytometry), viability and fold expansion prior to entering the HSC-macrophage differentiation protocol. HSC entered the differentiation protocol on Day 0 (DO) then were directed to differentiate over a 10-day (D10) period using a cocktail of growth cytokines including recombinant macrophage colony-stimulating factor and recombinant human granulocyte / macrophage colony-stimulating factor. Post differentiation (D10), the macrophage phenotype was confirmed using flow cytometry for CD45+ and CD11 B+ expression, viability and visual phenotype.

[0252] To prepare cells for testing, cells were taken from the culture environment and tested directly on the instrument. AuraCyt™ (dielectric) signatures were generated for DO HSCs and D10 HSC-derived macrophages representing the start and end of the differentiation protocol, respectively. AuraCyt™ (dielectric) signatures from DO and D10 were compared to one another using the multivariate Hotelling’s T squared comparative statistic where a significant difference was reported as p<0.05. Scatter plots displaying shifts in DO and D10 cell populations are presented as a PCA scatter plot; see Figure 11.

[0253] Characterisation of Mixed Heterogeneous Cell Populations Using AuraCyt™ (dielectric) signatures

[0254] Data were collected for beads (calibration) and cells on every test day. Data were collected over 6 test days. Data were collected across two instruments and two modules. Bead data were analysed first (Figure 12A) and used to compensate the system to ensure consistency of instrument and module performance prior to cell sample analysis (Figure 12B). This included eliminating any tests with temperature drift. Cell samples were analysed in triplicate (technical replicates) using the Celledonia™ platform, Cell types included: Jurkat cells (CD3, CD4), KG-1 cells (CD34) and THP-1 cells (CD14, CD32). Each line was tested individually to generate a unique signature for each line. Using this signature, a gate was generated for each line (Figure 13A). A mixed population was then generated by mixing each of the three cell types in a 1 :1 :1 mix (Jurkat, KG-1 , THP-1). This mix was generated to model apheresis product which has a heterogeneous composition (Figure 13B).

[0255] QC analysis of all cell data was conducted to determine run and technical replicate variability. Only data passing the QC criteria was included to the gating investigation with data visualisation performed via t-SNE in Maestro. FCS express was investigated as a potential gating method for fixed gates. Concurrently, cell line identity was confirmed through flow cytometry, verifying the expression of known surface markers (data not shown).

[0256] Measurement to distinguish cells producing productive versus non-productive capsids

[0257] HEK293T cells were cultured in accordance with standard procedures and transfected with one of the following: Condition 1 - LVV-CAR: Cells transfected with all four required plasmids for LW-CAR production (VSVg, rev, gag-pol, CAR). A high-titre transfer plasmid containing the gene of interest (GOI) was used where possible. This is the productive capsid.

[0258] Condition 2 -Virus Like Particles (VLP): Cells transfected omitting the transfer plasmid (GOI), resulting in VLP production (VSVg, rev, gag-pol). This line models a non-productive capsid product. Condition 3 - Control: Un-transfected cells resulting in no LVV production. Samples were taken at three time points: pre-transfection Oh, 24 hours and 48 hours, post- transfection.

[0259] Cell samples were analysed in triplicate following standard protocols using the Celledonia device and AuraCyt™ signatures were generated for each cell population (Figure 14A). Differences between populations were determined by Effect Size which was measured using Cohen’s d statistical measure (standardised method of measuring the difference between two group means helping to understand the magnitude of the difference, regardless of the sample size). Effect size for each timepoint was calculated for each condition; control, productive capsid and non-productive capsid (Figure 14B).

[0260] System calibration and QC Lentivirus Transfection

[0261] Bead data were analysed first (AM beads) and used to compensate the system to ensure consistency of instrument and module performance prior to cell sample analysis. To account for bead drift (AM to PM) and to a credible difference between cell populations, effect size of the beads (from AM to PM) was calculated for each test day (0, 24h and 48h). If the bead effect size was larger than the test cell effect size, this was deemed a ‘non-credible’ population shift or ‘no difference’. QC analysis of all cell data was conducted to determine run and technical replicate variability. Only data passing the QC criteria was included to subsequent analysis.

[0262] Selection of optimal viral vector host lines (HEK293) by predicting contaminating exosome release

[0263] This project aimed to assess whether AuraCyt signatures could differentiate between a wild type HEK 293T cell line that releases high exome levels (HEK293T) and a proprietary HEK293 cell line that releases low exosome levels (LowExo). Standard cell culture and harvest procedures were used to generate samples of HEK293T and LowExo cells for testing. Cell samples were collected over 3 test days (D1 , D2, D3) and run in triplicate on the Celledonia™ instrument and subsequently analysed to generate AuraCyt™ signatures (Figure 15A). To account for bead drift caused by temperature fluctuations, data was only included to the analysis if the mean temperature difference was low over the testing period. Bead data were analysed first and used to compensate the system to ensure consistency of instrument and module performance prior to cell sample analysis. QC analysis of all cell data was conducted to determine run and technical replicate variability. Only data passing the QC criteria was included to subsequent analysis. A T-test was performed and effect size measured to see the magnitude of change between two cell lines over the test period (Figure 15B).

[0264] Predictive Monitoring of Lentiviral Vector Productivity using AuraCyt™

[0265] To investigate whether AuraCyt™ could predict lentiviral productivity during manufacture, the following study was performed. A high-producing HEK293T cell line (Figure 16A) and a LowExo variant (Figure 16B) were each assigned to the following conditions: (1) HEK293T - Control (untransfected) (2) HEK293T - test -LVV-GFP transfected (3) LowExo - Control (untransfected) (4) LowExo - test - LW-GFP transfected. Cells were grown under standard culture conditions and sampled at 24- and 48-hours post-transfection, and Celledonia™ was used to generate AuraCyt™ signatures for each condition. Effect size: was calculated to show level of difference between the transfection condition and control samples at each timepoint for each cell line. QC analysis of all cell data was conducted to determine run and technical replicate variability. Only data passing the QC criteria was included to subsequent analysis. A T-test was performed and effect size measured to investigate the magnitude of change between two cell lines over the test period (Figure 16C). This would provide a gauge of productivity of each cell line.

[0266] Example 1

[0267] Cell line discrimination using AuraCyt™ signatures

[0268] AuraCyt™ technology demonstrated that 3 biologically different cell lineages, CHO, THP-1 and Jurkat, returned distinct signatures, both at the single cell and population levels that located within distinct regions of a PCA scatter plot averaging 25 events (Figure 1A). THP-1 cells shown in lower left gate, Jurkat cells in lower right gate and CHO cells in the top gate. Concurrent testing by flow cytometry, the industry recognised method for cell characterisation, confirmed that each line expressed the universally recognised markers associated with each individual cell type. THP-1 cells were confirmed by dual stain of CD32 and CD4 (99.65%, positive, Figure 1 B); CHO cells were confirmed by integrin B5 stain (99.972% positive; Figure 1C) and Jurkat cells were confirmed by dual stain of CD3 and CD4 (72.113% positive, Figure 1 D). This providing confidence that the cells obtained from established global repositories remained in their optimal state throughout experimentation.

[0269] Investigation of the frequency response data generated using AuraCyt™ showed distinct separation of each cell type in the high frequency range pertaining to differences in intracellular complexity and thus enabling clear discrimination of cell lines from one another based on AuraCyt™ signatures. Figure 1 E shows technical replicates of THP-1 cells (top traces x 2), CHO cells (middle traces x 2) and Jurkats (bottom traces x 4).

[0270] To provide confidence in test robustness (Figure 1 F) THP-1 and CHO cells AND THP-1 and Jurkat cells were compared using Normalised Mean Root Square Deviation (NMRSD) analysis to determine variance throughout data collection (columns 0-2), between technical replicates (columns 3-5) and between cell lines (THP-1 vs CHO cells = columns 6-11) and (THP-1 vs Jurkat cells = columns 12-23). The low variance for data collection and between technical replicates show robust data generation and the high variance between data of different cell types confirms that different cell populations can be clearly discriminated from one another.

[0271] From the data presented, AuraCyt™ technology can generate distinct cell signatures (at both the single cell and population level) for biologically distinct cell lineages. Credence to the generated signatures was supported by flow cytometry for known cell surface markers and by demonstrating low variance for robust data generation throughout the test period and between technical replicates. Assessing cells at different frequency ranges can clearly discriminate subtle changes such as intracellular complexity in the high frequency range.

[0272] Example 2

[0273] Cell health status assessment using AuraCyt™ signatures

[0274] AuraCyt™ signatures were generated for live and apoptotic THP-1 cell conditions in a controlled apoptosis induction study. Cells were tested concurrently on Celledonia™ and by flow cytometry for known markers that identify cell health status, PI and Annexin V. Specifically, live cells with intact membranes will not express phosphatidyl serene as part of their outer cell membrane, a marker of apoptosis and will exclude propidium iodide, a marker of late phases of apoptosis and onset of necrosis. Therefore, healthy cells will not stain for either marker. A dual stain of PI and Annexin V was performed on both live and apoptotic cells. AuraCyt™ signatures, generated for each cell condition (live or apoptotic), are presented in Figure 2 as principal component analysis (PCA) for live (elliptical gate bottom right, broken line) and apoptotic (elliptical gate top left) TH P-1 cells. Distinct separation is observed between populations of each health cell status when comparing AuraCyt™ signatures which was clearly defined by gating. Corresponding flow cytometry analysis is shown for live cells (Figure 3) where cell populations were <3% positive for Annexin V and PI so are considered ‘healthy’. In addition, flow cytometry analysis of TH P-1 cells, subjected to induced apoptosis by an 18- hour Camptothecin treatment stained 55.22% positive for PI and Annexin V confirming the apoptotic phenotype (Figure 4). This analysis provides confidence that AuraCyt™ can detect apoptotic cells which correspond to flow cytometry analysis, the gold standard method of cell characterisation. Differentiating between live and apoptotic cells in real time without labelling will offer huge benefits to the biotechnology industry and has the potential to be configured into a standard assay for the detection of cell health powered by AuraCyt™.

[0275] Example 3

[0276] Discrimination of complex cell mixes using AuraCyt™ technology

[0277] PBMCs contain a complex mixture of white blood cell types present in donor peripheral blood including T-cells, B-cells, monocytes, natural killer cells and progenitor populations. PBMCs play a vital role in the understanding of immune function, vaccine development, infectious disease and haematological malignancies. As a result, these cells are crucial to researchers and clinicians for oncology, immunology, therapeutic drug discovery, and cell and gene therapy development and clinical application. When unsorted PBMCs were assessed directly by AuraCyt™ technology and the dimensionally reduced dataset was analysed by FCS express, distinct cell populations could be visualised on the returned LIMAP scatterplot. These populations could then be gated to return the number of cell events with that gate which were reported as a percentage of the total PBMC population (Figure 5). In addition, specific AuraCyt™ signatures were generated from the gated populations to identify specific cell types of interest (data not shown) using the spectral plotting function of FCS express. Concurrent flow cytometry analysis confirmed that the starting PBMC population contained distinct cell populations based on cell surface marker expression (Figure 5). This study indicates that AuraCyt™ can identify distinct cell populations from a heterogeneous mix without the requirement for labels and can be used with compatible software programmes to gate specific populations of interest for deeper investigation and / or the generation of population specific AuraCyt™ signatures for assay development. Example 4

[0278] Distinguishing cell types from one another using AuraCyt™ Technology

[0279] Continuous cell lines, both adherent and in suspension, such as Jurkat, THP-1, A549, Kelly and MDCK are used across the field of biotechnology for cell line development, immunotherapy and drug discovery. However, cell characterisation of multiple cell types can result in labour intensive cell assays and validation strategies e.g. flow cytometry or multi omics. Therefore, alleviating this requirement with simple, label free cell characterisation is an attractive option for the biotechnology sector.

[0280] To show how AuraCyt™ could address this requirement, distinct AuraCyt™ signatures were generated for each of the 5 cell lines described above under optimal culture and passage conditions. Observation of the returned LIMAP scatterplots confirmed that each cell lineage occupied a distinct region of the plot (data not shown). A quantitative assessment demonstrating statistical significance of similarities or differences between cell lines was performed using a modified chi-square test where significant differences were reported as Tx >60. In this study, the AuraCyt™ signature generated for the A549 cells was used as the control against which all other cell line signatures were compared (Figure 6). From the data presented, all cell lines were significantly different to the control whereas test A549 cells returned a signature that was significantly ‘no different’ to the control A549 signature. This indicates that AuraCyt™ signatures are inherent and unique to the cells under investigation, they can be generated for any cell in a single suspension (from suspension cultures or disaggregated adherent cells) and can be used in simple assays for cell line identification.

[0281] Example 5

[0282] Cell culture monitoring and Longitudinal analysis of cell cultures using AuraCyt™ signatures

[0283] To investigate AuraCyt™ signature robustness further and to assess if AuraCyt™ signatures could be used to track or monitor cells through a manufacturing event or prolonged passage, a controlled study was performed using AuraCyt™ signatures generated from Jurkat and THP- 1 cells over the course of 20 days. Day 0 (DO) was used as the control against which all other test days were compared for each cell type. Cells were grown under optimal conditions and tested every passage day to ensure experimental consistency and optimal cell growth. Cells were not cultured above passage 30. Figure 7A shows the longitudinal analysis of AuraCyt™ signatures of Jurkat cells and how these signatures remained stable over time (no significant difference in profile from Day 0 to Day 20 in culture where Tx <60). Figure 7B returns the same result for AuraCyt™ signature stability for THP-1 cells (Tx <60). To provide confidence that cell lines could be distinguished from one another, AuraCyt™ signatures from THP-1 cells were compared against the AuraCyt™ signatures generated for the Jurkat cells where the Jurkat signature from DO was used as the control. AuraCyt™ signatures from 4 test days were compared. Here, Jurkat cells always remained statistically similar (Tx <60) to the control (Jurkat DO) whereas, the THP-1 cells were always statistically different (Tx>60) (Figure 7C).

[0284] This data confirms that AuraCyt™ signatures are robust and can be used to identify cell lineages of interest. In addition, AuraCyt™ can be used as a simple yet powerful tool to monitor cells as they grow in culture. A defined AuraCyt™ control signature can be generated for cells as they grow optimally in culture, unknown cell samples can be compared against this control to indicate how similar they are to the control and whether or not the manufacturing event / culture is on track. This can lead to optimal process control strategies for manufacturing under bioreactor conditions and integration of artificial intelligence and machine learning correctives.

[0285] Example 6

[0286] Macrophages are a type of white blood cell that play a key role in the human immune system by protecting the body from infection, enabling regulation of tissue homeostasis by engulfing dying cells or toxic materials, mediating tissue repair and aiding in the prevention of neurodegenerative disorders. In vivo, macrophages are derived from haematopoietic progenitors that differentiate to monocytes which subsequently mature to macrophage lineages. Functional macrophages can also be differentiated directly from expanded HSC in vitro for therapeutic purposes. In this study, AuraCyt™ technology demonstrated that statistically distinct signatures (p< 0.05) could be generated for both undifferentiated HSC (DO) and HSC-derived macrophage populations (D10) where each population was located at a distinct area of the PCA scatter plot (Figure 11). Cell differentiation was confirmed with expression of known flow cytometry markers (data not shown) for HSCs (CD34+ expression > 90%) and HSC-derived macrophages (CD45+ and CD11 b+ expression; both > 90%). This demonstrates that AuraCyt™ has the potential to monitor cells as they differentiate from one cell state to another unlocking huge potential for the manufacture of immunotherapies and regenerative medicines by generating signatures that can predict optimal differentiation strategies, determine optimal harvest time or enable real-time correctives. Example 7

[0287] Donor cell variability remains a major challenge, as apheresis products differ in suitability for applications like iPSC generation, CAR-T, or immunotherapy — making it difficult to align input material with therapeutic goals. To model the complexity of apheresis product, Jurkat (T-cell line), THP-1 (monocyte cell line), and KG1 (macrophage cell line) were selected to represent key immune and hematopoietic cell populations relevant to cell therapy. Each cell line was measured individually and in a 1 :1 :1 mix using AuraCyt™. Prior to assessing cell data, compensation of the instrument and module was performed using beads via Maestro to effectively minimise instrument-to-instrument variation; see Figure 12. A, bead data prior to compensation. One outlier test (in purple) was eliminated from the analysis due to high temperature fluctuations. All other bead temperature data were consistent throughout the test period, preventing any impact from bead drift. Figure12B shows bead data post compensation with consistent alignment of AuraCyt™ signature. Cell data was aligned using this compensation setting prior to gating.

[0288] After calibration, dimensional reduction algorithms were applied to the cell data, with t-SNE selected for its ability to generate clear visual outputs. Analysis of the individual cell types allowed for the creation of distinct gating regions (Figure 13A), revealing unique signatures for each cell population. Using these gates, the mixed cell samples were analysed. The mixed cell population fell directly within the gates generated for the individual cell types enabling the discretion of each cell type (Figure 13B). The cells in the mixed sample were evenly distributed across three distinct regions, confirming the 1 :1 :1 ratio. This indicates that the AuraCyt™analysis platform can differentiate and identify multiple cell populations within heterogeneous mixtures without the requirement for labels.

[0289] To test fixed gating on an alternative analysis platform, data from AuraCyt™ were imported and plotted using standard flow cytometry software, FCS Express. However, the FCS fixed gates lacked sensitivity due to the reduction of dimensions from 511 (from AuraCyt™) to 16 in FCS Express, leading to key information loss and poor cell characterisation. This caused overlap between cell types, making predictive analysis challenging with FCS express. The clarity of message returned by the AuraCyt™ platform is demonstrably more sensitive than existing technologies and software for analysing large and complex data sets obtained by label free cell sensing.

[0290] Example 8

[0291] The lentiviral manufacturing industry is limited by the absence of rapid, predictive tools to optimise critical stages of viral vector production procedures. This study aimed to investigate the ability of AuraCyt™ to determine product quality by identifying productive capsids when compared to non-productive and control conditions. When comparing each condition to one another, statistically significant differences in AuraCyt™ signatures (P<0.05) were detected between all three conditions at 24 and 48 hours (Figure 14A). Any differences between populations were determined by effect size using Day 0 as a benchmark against which all test timepoints were compared. This was performed for each cell condition individually (Figure 14B). Control cells did not change in culture (P>0.05) whereas effect size increases steadily over the manufacturing time for both productive and non-productive conditions, a response consistent with viral particle production. In addition, productive capsid was significantly different (P<0.05) to both the control and the non-productive conditions indicating that AuraCyt™ signatures could be used to monitor cells in culture enabling early detection of productivity. These results support a fail-fast approach to viral vector manufacturing to improve upstream quality control, reduce purification burden, and minimizing downstream failures.

[0292] Example 9

[0293] Exosome contamination in lentiviral vector production poses a significant challenge by copurifying with viral particles due to their similar size and density. This not only reduces the purity and efficacy of the final product but also complicates downstream analyses and regulatory approval processes. Current methods for assessing exosome release are timeconsuming and labor-intensive resulting in a requirement for low exosome producing host lines. This study aimed to investigate if AuraCyt™ signatures could identify producer lines with reduced exosome release. Standard HEK293T and a proprietary low exosome-releasing variant (LowExo HEK293T) were cultured under identical conditions and assessed daily using AuraCyt™ over three consecutive days post-passage (D1-D3). Post calibration, PCA scatterplots were generated for each timepoint (Figure 15A) and LowExo cells were compared against HEK293WT cells to calculate an effect size (Figure 15B) that was indicative of a population change. From the data presented, a significant shift (P<0.05) could be observed between high and low exosome producing lines across all test days and the magnitude of this difference increased over time as shown by the effect size (Figure 15B). This aligns with the known correlation between time post-passage and elevated exosome release as reported by the developer in this lentiviral vector workflow.

[0294] This enables the developer to predict lines that produce low exosome levels prior to transfection to minimise downstream contaminants within the purified product. Alternatively, if exosome contamination is known to be risk factor during the manufacturing event, this would allow the developer to select a stringent purification procedure downstream to mitigate. These results confirm that Celledonia™ can sensitively track exosome-associated cellular changes, providing a powerful tool for host cell line selection and downstream impurity reduction.

[0295] Example 10

[0296] A major limitation in lentiviral vector production is the lack of in-process analytics to rapidly monitor productivity. This prevents optimal harvest timing and delays the detection of batch failures, leading to reduced yields and increased production costs. To investigate whether AuraCyt™ could predict and monitor lentiviral productivity during manufacture, two producer lines, HEK293T cells and Low Exo cells were transfected with LW-GFP plasmids and tested at 24h and 48h post transfection. Non-transfected cells from each condition were tested at each timepoint to act as a control. Data was compensated prior to analysis to account for instrument and module variability over the test period. PCA scatterplots were generated for HEK293T cells and Low Exo cells as shown by Figures 16A and B respectively.

[0297] From the data presented AuraCyt™ detected significant shifts (p < 0.05) between Control and LVV-GFP-transfected conditions which appeared within 24 hours of transfection in LowExo cells and 48 hours in HEK293T cells. These shifts intensified over time, consistent with the developer’s observations that lentiviral production increases steadily in the 48 hour time period post-transfection.

[0298] Interestingly, at the 48 hour timepoint, transfected HEK293T cells returned an AuraCyt™ effect size 2.3 times greater than the effect size shown by the transfected Low Exo cells (Figure 16C). This is consistent with the developer’s observation that transfected HEK293T cells produce 2-2.5 times more lentivirus than LowExo cells. These findings position AuraCyt™ as a predictive tool for monitoring productivity, optimising harvest timing, and improving batch quality decisions in viral vector manufacturing.

Claims

CLAIMS1 A method for the identification and analysis of eukaryotic cells, or subcellular part thereof, under test of more than one cell type in one or more cell culture media using impedance or dielectric spectroscopy comprising the steps: providing an electric stimulus signal having at least one component at a first frequency to at least one stimulus electrode, such that the at least one stimulus electrode generates a pre-determined, electrodynamic field including the first frequency that is applied to a cell under test of a first eukaryotic cell type in a cell culture medium; sensing a response electrodynamic field by means of at least one sensing electrode and providing a corresponding electric response signal to a sensing circuit, and obtaining a first output signal corresponding to said eukaryotic cell under test of the first eukaryotic cell type; providing said electric stimulus signal to at least one stimulation electrode, such that the at least one stimulus electrode generates said pre-determined, electrodynamic field that is applied to a eukaryotic cell under test of a second, differentcell-type in a cell culture medium; sensing a response in the electrodynamic field by means of at least one sensing electrode and providing a corresponding electric response signal to the sensing circuit, and obtaining a second output signal corresponding to said different cell type; comparing the first and second output signals to determine a measure of differentiation between said first and second cell-types; wherein the electric stimulus signal and the electrodynamic field has at least one frequency component that is greater than 0.15 GHz.

2. The method according to claim 1 wherein said at least one frequency component is between 0.15GHz and 10GHz.

3. The method according to claim 1 or 2 wherein said first eukaryotic cell and second celltype is contained in the same cell culture medium as separate cultures.

4. The method according to claim 1 or 2 wherein said first eukaryotic cell and said second cell type is a mixed culture contained in the same cell culture medium.

5. The method according to any one of claims 1 to 4 wherein said second cell type is a eukaryotic cell.

6. The method according to claim 5 wherein said first and / or second eukaryotic cell type is selected from the group: a mammalian cell, a plant cell an insect cell or a fungal cell.

7. The method according to claim 5 or 6 wherein said first and / or second mammalian cell is a cancer cell.

8. The method according to any one of claims 1 to 7 wherein said first and / or second mammalian cell is an apoptotic cell.

9. The method according to any one of claims 1 to 7 wherein said first and / or second mammalian cell is a stem cell.

10. The method according to claim 9 wherein said stem cell is a pluripotent stem cell, for example an embryonic stem (ES) cell or embryonal germ (EG) cell or an induced pluripotent stem cell.

11. The method according to claim 9 wherein said stem cell is a multipotent stem cell.

12. The method according to claim 1 wherein said multipotent stem cell is a haemopoietic stem cell.

13. The method according to claim 12 wherein said haemopoietic stem cell is a monocyte capable of differentiation into a macrophage.

14. The method according to any one of claims 9 to 13 wherein said stem cell is obtained from a human subject.

15. The method according to claim 14 wherein said differentiated haemopoietic cell is a myeloid cell.

16. The method according to claim 15 wherein said differentiated haemopoietic cell is a myeloid cell selected from the group: red blood cells, platelets, monocytes, and granulocytes, neutrophils, eosinophils, and basophils.

17. The method according to claim 14 wherein said differentiated haemopoietic cell is a lymphoid cell.

18. The method according to claim 17 wherein said haemopoietic cell is a lymphoid cell selected from the group: T cells, B cells, and natural killer (NK) cells, dendritic cells and mast cells.

19. The method according to any one of claims 14 to 18 wherein said cell culture medium is an apheresis medium obtained from a subject.

20. The method according to any one of claims 1 to 6 wherein said first eukaryotic cell type and / or second cell type is infected with a pathogenic microbe or virus.

21. The method according to any one of claims 1 to 6 wherein said first eukaryotic cell type and / or second cell is a plant cell.

22. The method according to any one of claims 1 to 6 wherein said first eukaryotic cell type and / or second cell is a microbial cell.

23. The method according to any one of claims 1 to 4 wherein said second cell type is a prokaryotic cell.

24. The method according to any one of claims 1 to 23 wherein said first eukaryotic cell type and / or said second cell type is a transgenic cell.

25. The method according to claim 24 wherein said first eukaryotic cell type and / or second cell type is a transfected mammalian cell.

26. The method according to claim 25 wherein said first and / or second cell is a mammalian cell transfected with a viral based vector.

27. The method according to claim 26 wherein said viral based vector is an adenovirus vector.

28. The method according to claim 26 wherein said viral based vector is an adeno- associated virus [AAV],29. The method according to claim 26 wherein said viral based vector is a lentivirus-based vector.

30. The method according to any one of claims 25 to 29 wherein said first and / or second mammalian cell is a Human Embryonic Kidney (HEK) cell.31 . The method according to any one of claims 25 to 29 wherein said first and / or second mammalian cell is a Chinese Hamster Ovary cell.

32. The method according to any one of claims 25 to 31 wherein said method compares transfection efficiency by said viral based vector between said first and / or second mammalian cell.

33. The method according to any one of claims 25 to 31 wherein said method compares the production of exosomes between said first and / or second mammalian cell after transfection with said viral based vector.

34. The method according to any one of claims 1 to 33 wherein the electric stimulus signal has a plurality of components at different frequencies, such that the at least one stimulus electrode generates a pre-determined, electrodynamic field including the plurality of different frequencies that is applied to the cells under test in one or more cell culture media.

35. The method according to any one of claims 1 to 34 wherein the electric stimulus signal comprises a pseudo-random binary sequence having a length and data rate that provide the pre-determined, electrodynamic field with a range of different frequencies.

36. The method according to any one of claims 1 to 35 wherein the output signal of each cell measurement comprises a point or vector in multidimensional space for that particular cell.

37. The method according to claim 36 wherein the comparison between the first and second output signals to determine a measure of differentiation between said first and second cell-type comprises a comparison of a point or vector in multidimensional space for each cell or a comparison of points or vectors in multidimensional space for first and second cell populations.

38. The method according to any one of claims 1 to 37 wherein the electrodes are exposed to and conduct into the cell culture medium.

39. The method according to any one of claims 1 to 38 wherein the electrodes and the sensing circuit are each part of an integrated circuit including an electrode array, the integrated circuit comprising layers of semiconductor.

40. The method according to claim 39 wherein the integrated circuit comprises an outermost passivation layer that does not extend over the electrodes, such that the electrodes are exposed to and conduct into the cell culture medium.41 . The method according to any one of claims 1 to 40 wherein the measurement comprises: a fluid passageway for a fluid medium and any cells therein; at least one stimulus electrode and at least one sensing electrode providing at least one measurement capacitor, operative through at least one part of the fluid passageway; a stimulation apparatus electrically coupled to the at least one stimulus electrode and applying an electric stimulus signal to the at least one stimulus electrode; and a sensing circuit having an input coupled to the at least one sensing electrode, and an electric response signal generated at an output.

42. The method according to claim 41 wherein the measurement comprises a first stimulus electrode and a first sensing electrode providing a first measurement capacitor, operative through a first part of the fluid passageway or a first fluid passageway; a second stimulus electrode and a second sensing electrode providing a second measurement capacitor, operative through a second part of the fluid passageway or a second fluid passageway; the first sensing electrode being electrically connected to the second sensing electrode; the stimulation apparatus being electrically coupled to the stimulus electrodes and simultaneously applying first and second electric stimulus signals to the first and second stimulus electrodes respectively, the first and second electric stimulus signals having the same form and opposite polarity; and the sensing circuit having an input coupled to the electrical connection between the first and second sensing electrodes, and an electric response signal generated at an output.

43. A method for the measurement and analysis of at least a first eukaryotic cell type, or subcellular part thereof, and a second cell type, or subcellular part thereof, under test in one or more cell culture media using impedance or dielectric spectroscopy comprising the steps: i) providing measurement apparatus comprising a first stimulus electrode and a first sensing electrode providing a first measurement capacitor, operative through a first part of a fluid passageway or a first fluid passageway; a second stimulus electrode and a second sensing electrode providing a second measurement capacitor, operative through a second part of a fluid passageway or a second fluid passageway; the first sensing electrode being electrically connected to the second sensing electrode; a stimulation apparatus electrically coupled to the first and second stimulus electrodes; and a sensing circuit having an input coupled to the electrical connection between the first and second sensing electrodes, and an output for providing an output signal; ii) providing first and second electric stimulus signals having at least one component at a first frequency simultaneously to the first and second stimulus electrodes respectively, the first and second electric stimulus signals having the same form and opposite polarity, such that the first and second stimulus electrodes generate a pre-determined, electrodynamic field including the first frequency that is applied to a cell under test of a first eukaryotic cell type in a cell culture medium; iii) obtaining from the output of the sensing circuit a first output signal corresponding to said cell under test of the first eukaryotic cell type; iv) providing said first and second electric stimulus signals simultaneously to the first and second stimulation electrodes respectively, such that the first and second stimulus electrodes generate said pre-determined, electrodynamic field that is applied to a cell under test of a second, different eukaryotic cell-type in a cell culture medium; v) obtaining from the output of the sensing circuit a second output signal corresponding to said different cell type; vi) comparing the first and second output signals to determine a measure of differentiation between said first and second cell-type;wherein the electric stimulus signal and the electrodynamic field has at least one frequency component that is greater than 0.15 GHz.

44. A method for the measurement and analysis of at least a one prokaryotic cell type, or subcellular parts thereof, and a second cell type, or subcellular parts thereof, under test in one or more cell culture media using impedance or dielectric spectroscopy comprising the steps: i) providing measurement apparatus comprising a first stimulus electrode and a first sensing electrode providing a first measurement capacitor, operative through a first part of a fluid passageway or a first fluid passageway; a second stimulus electrode and a second sensing electrode providing a second measurement capacitor, operative through a second part of a fluid passageway or a second fluid passageway; the first sensing electrode being electrically connected to the second sensing electrode; a stimulation apparatus electrically coupled to the first and second stimulus electrodes; and a sensing circuit having an input coupled to the electrical connection between the first and second sensing electrodes, and an output for providing an output signal; ii) providing first and second electric stimulus signals having at least one component at a first frequency simultaneously to the first and second stimulus electrodes respectively, the first and second electric stimulus signals having the same form and opposite polarity, such that the first and second stimulus electrodes generate a pre-determined, electrodynamic field including the first frequency that is applied to a cell under test of a first prokaryotic cell type in a cell culture medium; iii) obtaining from the output of the sensing circuit a first output signal corresponding to said cell under test of the first prokaryotic cell type; iv) providing said first and second electric stimulus signals simultaneously to the first and second stimulation electrodes respectively, such that the first and second stimulus electrodes generate said pre-determined, electrodynamic field that is applied to a cell under test of a second, different prokaryotic cell-type in a cell culture medium; v) obtaining from the output of the sensing circuit a second output signal corresponding to said different cell type;vi) comparing the first and second output signals to determine a measure of differentiation between said first and second cell-type; wherein the electric stimulus signal and the electrodynamic field has at least one frequency component that is greater than 0.15 GHz.

45. The method according to claim 44 wherein said at least one first cell type is a prokaryotic cell type and said second cell type is a prokaryotic cell type.

46. The method according to claim 44 wherein said at least one first cell type is a prokaryotic cell type and said second cell type is a eukaryotic cell type.

47. The method according to claim 46 wherein said first cell type is a prokaryotic cell type and said second cell type is a microbial eukaryotic cell type.

48. The method according to claim 47 wherein said eukaryotic microbial cell type is a fungal cell type.

49. The method according to any one of claims 44 to 48 wherein said prokaryotic cell is a bacterial cell.

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