Biosensors using particle motion

Abstract

The present invention relates to a biosensor device for sensing an analyte over a period of time using particle motion, having a functionalized surface and particles, the biosensor device having a first state in which the particles are associated with the surface and a second state in which the particles are not associated with the surface, switching between the first and second states being dependent on the presence, absence and / or concentration of an analyte, whereby motional characteristics of the particles change in response to the presence, absence and / or concentration of the analyte, and properties of the particles and surface being selected such that in the second state the particles are within the vicinity of the surface and are not conjugated to the surface such that the biosensor can measure changes in spatial coordinate parameters of the particles relative to the surface.

Description

[Technical Field]

[0001] The present invention relates to a biosensor device for sensing an analyte over a period of time using particle motion. The present invention further relates to a method for sensing an analyte using particle motion, the use of the biosensor device of the present invention as a sensor in a method for sensing an analyte or on, in, or as part of another device. The present invention further relates to a biosensor device of the present invention for use in in vivo biosensing, ex vivo biosensing, or in vitro biosensing. [Background technology]

[0002] Biosensor devices for chemical or biochemical markers have typically been developed for use in in vitro diagnostics, where a sample is collected (e.g., blood, saliva, urine, mucus, sweat, or cerebrospinal fluid) and transferred to an artificial device (e.g., a plastic disposable) outside the body. In such biosensing assays, extensive sample pretreatment steps (e.g., separation or dilution steps) may be applied, and multiple reagents may be introduced into the assay (e.g., for target amplification, signal amplification, or washing steps). Examples of in vitro biosensing assays are immunoassays, nucleic acid tests, electrolyte and metabolite tests, electrochemical assays, enzyme activity assays, cell-based assays, etc. For a complete overview, see the Tietz textbook of clinical chemistry and molecular diagnostics (Connell, 2012, 5). th Please refer to the relevant edition.

[0003] In in vivo biochemical sensing, at least part of the sensor system remains connected to or is inserted into a living organism, e.g., the human body, for example, on, in, or under the skin, or on, in, or under another part of the body. Due to the contact between the biosensor and the living organism, in vivo biochemical sensing sets high requirements for biocompatibility (e.g., inflammatory processes should be minimized), and the sensor system should operate reliably within the complex environment of the living organism. For monitoring applications, the system must be able to perform two or more measurements over time, and the system must be robust and easy to handle.

[0004] A well-known application of in vivo biochemical sensing is continuous glucose monitoring (CGM). Commercially available continuous glucose monitoring devices are based on enzymatic electrochemical sensing (see, for example, Heo, Yun Jung, and Shoji Takeuchi; Towards smart tattoos: implantable biosensors for continuous glucose monitoring; Advanced healthcare materials 2(1), 2013: pp. 43-56). Enzymatic sensing is less common than affinity-based sensing. Commercially available systems for in vivo glucose monitoring are available, for example, from Dexcom and Medtronic.

[0005] The field of sensing and monitoring has many applications. Biological systems, such as cells, multicellular systems, organs, and organisms, as well as other systems and materials based on or containing biomolecules or cells, exhibit dynamics at the most fundamental level driven by time-dependent changes in bioorganic molecules, such as small molecules, metabolites, hormones, proteins, or nucleic acids. In some applications, it is highly beneficial to be able to monitor specific molecules that decisively reflect dynamics, allowing timely action to be taken and changes to be managed. Sensing technologies for measuring and monitoring biomolecules enable the study of dynamic changes in biological systems based on measured responses and the control of such systems, for example, in the fields of healthcare, bioengineering, and industrial processing. Sensors are available for continuously measuring pH, electrolytes, and metabolites, but not yet available for measuring low concentrations of biomolecules.

[0006] A well-known technique for measuring biomolecules and biomolecular interactions is tethered particle motion (TPM). TPM techniques are based on measuring the motion of particles tethered to a surface. An example of such a system is described by Laurens et al. (Dissecting protein-induced DNA looping dynamics in real time; Nucleic acids research 37(16), 2009: pp. 5454-5464), who reported TPM experiments on proteins bound to DNA tethers to reveal how the proteins alter DNA conformation. In such studies, measures are taken to avoid non-tethered attachment of particles to surfaces, since particles attached to surfaces by other means would not provide information about the tether.

[0007] Biosensors with functionalized tethers attached to a surface have been developed based on the principle that the motion of particles attached by the tether changes in response to the presence of an analyte. The change in motion is due to a change in the structure of the tether itself caused by the presence of the analyte. Some techniques detect analytes by measuring the kinetic properties of functionalized particles tethered to a surface in response to the presence of the analyte. In these techniques, it is important to avoid particle binding to the surface, as steric hindrance, which is affected by the analyte, can interfere with sensitivity.

[0008] Further biosensors based on TPM technology with functionalized particles and / or functionalized surfaces are described, for example, in the international patent application published under the number WO 2016 / 096901. [Prior art documents] [Patent documents]

[0009] [Patent Document 1] International Publication No. 2016 / 096901 [Non-patent literature]

[0010] [Non-Patent Document 1] Tietz textbook of clinical chemistry and molecular diagnostics(Connell,2012,5th edition) [Non-patent document 2] Heo,Yun Jung,and Shoji Takeuchi;Towards smart tattoos:implantable biosensors for continuous glucose monitoring;Advanced healthcare materials 2(1),2013:pp.43-56 [Non-patent document 3] Laurens et al. (Dissecting protein-induced DNA looping dynamics in real time; Nucleic acids research 37(16), 2009:pp.5454-5464) Summary of the Invention

[0011] In view of the biosensors described in the art, the present inventors have developed a novel biosensor device suitable for continuous, repetitive or intermittent sensing of an analyte over a period of time using particle motion. The present invention provides a biosensor device having a functionalized surface and particles, - the biosensor device has a first state in which the particles are associated with the surface and a second state in which the particles are not associated with the surface; - switching between said first state and said second state depends on the presence, absence and / or concentration of an analyte; whereby the motional properties of the particles can change in response to the presence, absence and / or concentration of the analyte, thereby enabling sensing of the analyte by measuring changes in spatial coordinate parameters of the particles relative to the surface; A biosensor device is provided. This has been found when the particle and surface properties are selected such that the particle is in proximity to the surface in the second state, allowing the biosensor to measure changes in the particle's spatial coordinate parameters relative to the surface. The phrase "proximity to the surface" can refer to the distance between the particle and the surface in the second state at which the biosensor can still measure changes in the particle's spatial coordinate parameters relative to the surface. It should be noted that this distance between the particle and the surface is not limited to any particular distance; the greater the distance between the particle and the surface, the less efficient the biosensor will be compared to a biosensor with a smaller distance between the particle and the surface. Preferably, the distance between the particle and the surface in the second state is at least 5 nm, more preferably in the range of 5 nm to 100 μm, and more preferably in the range of 5 nm to 10 μm. It has been found that further conjugation of the particle to the surface is not necessary. In other words, the present invention provides a non-tethered biosensor device suitable for use in a method for continuous sensing of an analyte.

[0012] It has been found that the biosensor device of the present invention allows continuous molecular biosensing without a fixed tether between the particle and the surface, even if the particle is not connected to the surface, for example, using a tether linker. That is, the particle remains close to the surface due to field forces, for example, due to a gravitational field. The particles of the biosensor device of the present invention exhibit Brownian motion, and their motion changes when the particles switch between an associated state and a non-associated state (also called a "dissociated state"). The particle's motion behavior and associated / dissociated state lifetime depend on the concentration of the target, i.e., analyte, in the solution.

[0013] As used herein, the term "conjugate" refers to the covalent attachment of a first molecule to a second molecule. The term "conjugate" also refers to the linkage of one portion of a biosensor device to another portion of the biosensor device, for example, the crosslinking of a particle of the biosensor device to the surface of the biosensor device via a linker or tether. As used herein, the phrase "particles not conjugated to a surface" refers to freely mobile particles that are not linked to a surface in a non-associated state.

[0014] As used herein, the term "biosensing" refers to the identification, testing, characterization, monitoring, and other measurement of analytes using biosensors.

[0015] As used herein, the term "analyte" refers to a substance being identified, tested, characterized, monitored, or otherwise measured, and can include molecules of a single target species (e.g., glucose) or molecules of multiple target species (e.g., glucose and synthetic deoxyribose nucleic acid (DNA)). Examples of analytes include latex beads, lipid vesicles, whole chromosomes, nanoparticles, extracellular vesicles, liposomes, viruses, cells, cell fragments, supramolecular objects, protein aggregates, and biomolecules including proteins and nucleic acids, gas molecules (e.g., ethylene), metal or semiconductor colloids and clusters, small molecules in the size range of a few nanometers to 10 nm, metabolites, and other such chemical molecules.

[0016] As used herein, the term "particle" can refer to an object with detectable motion in a fluid or viscoelastic matrix. Fluid or viscoelastic matrices are often simply referred to as fluids. Particles can be composed of, for example, organic materials (e.g., polymers, supramolecular systems, micelles, nanosomes), inorganic materials (e.g., oxides, silica, metals), or combinations thereof. They can have different internal and external shapes and architectures (e.g., spherical, rod-shaped, hollow, star-shaped, bubbles, hybrid systems, particles within a matrix, aggregates, regular or irregular). They can have a minor axis ranging from 1 nm to 15 μm, more preferably 5 nm to 5 μm, and more preferably 10 nm to 3 μm.

[0017] As used herein, the term "surface" can refer to an object relative to which coordinate parameters of particles, such as position, distance, translation, displacement, angle, orientation, rotation, translational velocity, or angular velocity, can be measured. A surface can be composed of, for example, organic or inorganic materials, or a combination thereof. It can have different shapes (e.g., flat, curved, corrugated) and different internal and external architectures (e.g., solid, porous, permeable, layered, flexible, viscoelastic).

[0018] With respect to surfaces suitable for use in the present invention, it is noted that the surface may be a planar surface, a surface having concave or convex structures, a chemically and / or physically patterned surface, particles, polymers, porous structures, or supporting structures such as a porous matrix, etc. It is emphasized that the surface may also be a three-dimensional structure.

[0019] As used herein, the phrase "particle and surface characteristics" refers to particle, surface, and fluid parameters that cause the particle to have a particle-to-surface distance in the second state, e.g., within a range of 5 nm to 10 μm. For example, particle parameters suitable for providing a biosensor of the present invention can include particle size and particle density. For example, surface parameters can include the selection of a surface material or type of material or design, such as acoustic, magnetic, transport, or mechanical properties. The phrase "particle and surface characteristics" also includes the interaction between the particle, surface, and fluid, i.e., the method of confining the particle to the surface, e.g., by weight, acoustic field, flow, mechanical confinement, etc., as well as corresponding properties such as density, temperature, applied field, mechanical design, etc.

[0020] As used herein, the term "biosensor" may refer to any suitable sensor used for biochemical, biological, chemical, electrochemical, or other testing.

[0021] As used herein, the phrase "surface-associated" refers to a non-covalent bond or attachment, meaning that the particles of the invention adhere, bind, or electrostatically attach to the surface of, for example, a biosensor device.

[0022] The biosensor device of the present invention may contain various amounts of particles. However, preferably, the biosensor device of the present invention may contain at least 10 particles, more preferably at least 100 particles. It has been found that by providing a biosensor device containing more than 10 particles, more preferably more than 100 particles, a robust and reliable biosensing method can be implemented. Furthermore, the biosensor device may be 415 x 415 μm. 2 It has been found that the density of particles can range from a few to several thousand particles within a region of 415×415 μm. 2 100 to 100,000 particles, more preferably 500 to 20,000 particles, even more preferably 415 x 415 μm 2The total area over which particles are tracked can preferably contain a particle density of 1,000 to 10,000 particles within a region of 0 ~10 8 μm 2 , more preferably 10 3 ~10 7 μm 2 , more preferably 10 4 ~10 6 μm 2 is.

[0023] For sensing the analyte, the biosensor device may include an optical system having a diffraction limit, the biosensor device including particles separated from nearest particles by at least the diffraction limit of the optical system.

[0024] The biosensor device of the present invention can perform binding assays, competitive assays, displacement assays, sandwich assays, enzymatic assays, assays involving target and / or signal amplification, multi-step assays, or assays involving molecular cascades.

[0025] As used herein, the term "functionalized" refers to the transformation of inert particles and / or surfaces into particles and / or surfaces with specific activity. In particular, the particles and / or surfaces may be functionalized with binding sites or moieties such as antibodies, aptamers, nanobodies, molecularly imprinted polymers, organic molecules, etc.

[0026] The particles of the biosensor device may be functionalized with a first moiety bound to the particle. Instead of having functionalized particles, the biosensor device may include a functionalized surface functionalized with a second moiety bound to the surface. When particle-functionalized or surface-functionalized first or second moieties are used, the moieties used have binding affinity for the analyte. By providing such a system, steric hindrance in the presence of the analyte moves the particle to the second state (i.e., the particle-surface non-associated state), and the absence of the analyte, and therefore the absence of steric hindrance, moves the particle to the particle-surface associated state (i.e., the first state of the present invention).

[0027] As used herein, the term "bound" refers to a bond or attachment, which may be covalent, e.g., by chemical coupling, or non-covalent, e.g., by ionic interactions, hydrophobic interactions, hydrogen bonding, etc. The covalent bond may be, e.g., an ester, ether, phosphoester, amide, peptide, imide, carbon-sulfur bond, carbon-phosphorus bond, etc. The term "bound" is broader than and includes terms such as "coupled," "fused," "associated," "linked," and "attached."

[0028] Alternatively, a biosensor device of the present invention can be provided in which both the particle and the surface are functionalized, i.e., the particle is functionalized with a first moiety bound to the particle and the surface is functionalized with a second moiety bound to the surface. In such a configuration of a biosensor device of the present invention, it is preferred that both moieties have a binding affinity for each other depending on the presence, absence, or concentration of an analyte. On the one hand, such a biosensor device can provide an analyte biosensing method in which, in the presence of an analyte, the functionalized particle is in its first state, i.e., associated with the functionalized surface. On the other hand, such a biosensor device can provide an analyte biosensing method in which, in the absence of an analyte, the functionalized particle is in its first state, i.e., associated with the functionalized surface.

[0029] With respect to the density of particles or surface-bound moieties, it is contemplated that any density may be suitable to provide a biosensor device suitable for use in a method of biosensing an analyte. Such surface densities are preferably in the range of 10 0 ~10 8 part / μm 2 Preferably, the biosensor device may be 1 ~10 7 part / μm 2 and preferably the moieties bound to the particle or surface are in the range of 10 1 ~10 7 part / μm 2 , 10 2 ~10 6 part / μm 2 or 10 3 ~10 5 part / μm 2 It has a density in the range of

[0030] The first or second moiety may be selected from the group consisting of a protein, an antibody, a fragment thereof, a recombinant protein, a peptide, a carbohydrate, a saccharide, a molecularly imprinted polymer, a small molecule, a nucleic acid, a DNA molecule, a PNA molecule, an aptamer, a nanobody, a multivalent binding agent, or a combination thereof. Preferably, the first or second moiety is selected from the group consisting of a binding molecule for glucose, an electrolyte, a metabolite, a small molecule, a bioactive substance, a toxin, a lipid, a carbohydrate, a peptide, a hormone, a drug, a drug metabolite, a protein, an oligonucleotide, DNA, RNA, a nanoparticle, an extracellular vesicle, an exosome, a nanosome, a liposome, a virus particle, a cell, a cell fragment, a supramolecular object, or a protein aggregate.

[0031] In a further aspect, the present invention relates to the use of a biosensor device according to the present invention in a method for performing multiplexing, preferably analyte multiplexing, spatial multiplexing (e.g., spot multiplexing or chamber multiplexing), spectroscopic multiplexing, probe function multiplexing. Furthermore, the present invention relates to the use of a biosensor device according to the present invention as a sensor on, in, or as part of a system for sensing or monitoring, which may include, for example, an endoscope, a tube, a needle, a fiber, a catheter, a patch, a disposable probe, a wearable device, an internal device, a flow cell, or a disposable cartridge.

[0032] In another aspect, the invention relates to a biosensor device according to the invention for use in in vivo, ex vivo or in vitro biosensing or for monitoring assays using living cells, tissues or organs, such as in in vitro diagnostic testing, point-of-care testing, environmental testing, food testing, process monitoring, process control, forensic, biological, biomedical and pharmaceutical research.

[0033] In yet another aspect of the invention, the invention provides a method for sensing an analyte using particle motion, the method comprising the steps of: a) contacting a matrix containing an analyte with a biosensor device of the present invention; and b) detecting a motional characteristic of the particle that changes in response to the presence of the analyte; Including, the motion characteristics include spatial coordinate parameters of the particle relative to the surface; Regarding the method.

[0034] In considering the methods of the present invention, it is noted that the particles of the biosensor devices of the present invention are typically arranged to switch from a first state (i.e., particle-surface associated) to a second state (i.e., particle-surface non-associated) with an average effective dissociation time, and the particles of the biosensor devices of the present invention are typically arranged to switch from the second state to the first state with an average effective association time.

[0035] Furthermore, it has been found that controlling the flow of the analyte-containing matrix minimizes the net distance that particles can be displaced across the biosensor. Thus, the method of the present invention can further include a step in step b) in which the direction of the flow of the analyte-containing matrix is ​​changed continuously or intermittently. Such flow changes can include random flow direction changes or reverse flow direction changes.

[0036] As used herein, the terms "mean effective dissociation time" and "mean effective association time" refer to the average time required for a particle to dissociate from and associate with a surface, respectively. In other words, the average time required to reach a completely particle-surface non-associated state (i.e., the second state) and a particle-surface associated state (i.e., the first state), i.e., any type of association state, such as a single molecular bond (monovalent) or multiple molecular bonds (multivalent).

[0037] Considering the mean effective dissociation time and mean effective association time of particles to reach a bound or unbound state with the surface, in a preferred embodiment of the method of the present invention, step b) of detecting the particle's kinetic characteristics is performed over a period longer than the mean effective dissociation time and / or the mean effective association time. By providing a method in which the detection of the particle's kinetic characteristics is performed over a period longer than the mean effective dissociation time and / or the mean effective association time, a robust and reliable method is provided in which the events related to analyte sensing can be measured sufficiently to achieve good analyte sensing event statistics or for extraction of state lifetimes and state lifetime distributions.

[0038] The present invention describes a biosensor with single-molecule resolution. Sensors with single-molecule resolution provide signals with digital characteristics, also known as levels, states, transitions, switches, or events. Such digital signals obey the fundamental laws of Poisson statistics. This means, for example, that the coefficient of variation due to stochasticity can be scaled by 1 / square root (N), where N is the average number of detected events. This improves the statistics of detected events, reduces variation, and increases precision.

[0039] In state-of-the-art sensors, low concentrations are typically measured by using binding moieties with high affinity and / or low dissociation rate constants (low k_off). A low dissociation rate constant implies slow unbinding characteristics (long analyte bound-state lifetime), which is not informative when determining particle binding event statistics. To achieve good statistics (a large number of detected particle events N), the particle-state lifetime must not be too long; otherwise, insufficient events will be recorded in a given measurement time span.

[0040] In one embodiment of the present invention, statistics can be improved by having a bond with a relatively low dissociation rate constant (to enable measurement of low concentrations) and another bond with a relatively high dissociation rate constant (for a high N, i.e., good particle-event statistics). If the dissociation rate constants differ by approximately three-fold, dissociation of the analyte from the strongest binder (with the lowest dissociation rate constant) takes an average of three times longer than dissociation from the weakest binder (with the highest dissociation rate constant). Because of this time ratio, several particle binding and unbinding events may be observed during the time the analyte associates with the strongest binder (e.g., in a sandwich assay), or several particle binding and unbinding events may be suppressed during the time the analyte associates with the strongest binder (e.g., in a competitive assay). For example, assuming three unbinding events and three binding events, N is essentially 6, which can reduce the coefficient of variation by 1 / square root (6), significantly lower than 1. Therefore, due to the ratio between the dissociation rate constants, the variation is significantly smaller and the measurement is more accurate. [Brief explanation of the drawings]

[0041] [Figure 1] FIG. 1 shows a schematic diagram of a biosensor device of the present invention in which both particles 1 and surface 2 are functionalized with first moieties 3 and second moieties 4. An analyte of interest 5 is also visualized in FIG. 1. The biosensor device shown in FIG. 1 is in its second, dissociated state, in which functionalized particles 1 are not associated with functionalized surface 2. [Figure 2] Figure 2A shows a schematic diagram of a biosensor device of the present invention in which sensing of an analyte of interest 5 is measured using a sandwich assay, where the analyte of interest 5 is sandwiched between a first portion 3 of a particle 1 and a second portion 4 of a surface 2, causing the particle 1 to associate with the surface 2 (i.e., the first state of the present invention). Figure 2B shows a schematic diagram of a biosensor device in which the analyte 5 is not sensed by the biosensor. [Figure 3]3A shows a schematic diagram of a biosensor device of the present invention in which sensing of an analyte of interest 5 is measured using a competitive assay, with a first portion 3 of a particle 1 binding to a second portion 4 of a surface 2. FIG. 3B shows a schematic diagram of a biosensor device of the present invention in which sensing of an analyte of interest 5 is measured using a competitive assay, with the analyte of interest 5 binding to a portion 4 of the surface 2. [Figure 4] An example of a flow cell cartridge suitable for use as a biosensor device of the present invention is shown. The flow cell cartridge comprises an inlet 10, a flow channel 11, and an outlet 12. [Figure 5] Figure 5 shows the results of measurements of particles with a diameter of 1 μm in an oligonucleotide-based sandwich assay at a 125 pM ssDNA target concentration. The left panel of Figure 5 shows the 2D motion pattern reconstructed from the xy trajectory data. The center panel of Figure 5 shows the diffusion coefficient over time, illustrating free Brownian motion and two cases of confined Brownian motion caused by target-induced sandwich formation between the particle and the substrate. To distinguish between the unbound state (where the particle is not associated with the surface) and the bound state (where the particle is associated with the surface), a threshold value of D = 0.1 μm / s is set. The right panel of Figure 5 shows a histogram of the calculated diffusion coefficient values, showing a Gaussian-like distribution in the unbound state and a peak below the threshold for the bound state. In this configuration with 125 pM target (500 nM incubation concentration of substrate-side binder and 10 μM incubation concentration of particle-side binder), approximately 15% of all particles exhibit single-molecule binding. This increases to approximately 30% at a target concentration of 250 pM. It is further noted that measurements were initiated 2 minutes after addition of the target (the analyte sensed by the biosensor). [Figure 6]Figure 1 shows various diffusion coefficient histograms for an oligonucleotide-based sandwich assay using 1 μm diameter particles. In buffer (PBS), a Gaussian-like curve is observed with a mean D of approximately 0.25 μm / s. Upon addition of ssDNA target molecules, the particles are able to bind to the substrate in a sandwich format, thus decreasing the diffusion coefficient. This is reflected in the histogram by the appearance of a peak at D < 0.15 μm / s. The prominence of the peak increases with target concentration. [Figure 7] Figure 6 shows bound-state lifetime survival curves for the same experimental data. The graph shows the lifetimes (x-axis, lin scale) and their survival fractions (y-axis, log scale) at different target concentrations. The cumulative distribution function (CDF) of all bound-state lifetimes was calculated, and the survival fractions are taken as 1-CDF (the points in the graph). The characteristic bound-state lifetimes are extracted based on a biexponential fit of the bound-state lifetime survival curves (solid lines in the graph). The first exponent represents the short bound-state lifetime attributed to the single-molecule binding mode (τsm). This characteristic lifetime remains relatively constant upon target addition, as its lifetime depends solely on affinity binder properties. The second exponent represents the long-lived bound state attributed to multivalent binding (τmv). The fraction of multivalent binding and the characteristic lifetime observed in this experiment increase with increasing target concentration. [Figure 8] Figure 6 shows unbound state lifetime survival curves for the same experimental data. The graph shows the lifetimes (x-axis, linear scale) and their survival rates (y-axis, log scale) at different target concentrations. Similar to the bound state lifetimes, the characteristic unbound state lifetimes are extracted based on a double exponential fit of the unbound state lifetime survival curves (solid lines in the graphs). The first exponent (τ1) represents the short unbound state lifetimes (<10 s) attributable to nonspecific interactions and measurement and analysis artifacts, which are independent of target concentration. The second exponent (τ2) contributes to the unbound state lifetime associated with molecular binding, which is inversely proportional to target concentration. As target concentration increases, particles bind to the substrate more frequently, and the time between binding events decreases. This is reflected in a decrease in the characteristic unbound state lifetime. [Figure 9]A schematic diagram of the ssDNA sandwich assay experiment using PLL-PEG functionalization is shown. Particles were functionalized with a particle-side binder bearing an 11-bp sequence complementary to the ssDNA target. A DBCO-tagged substrate-side binder was coupled to the physisorbed PLL-g-PEG polymer via an incorporated azide group using second-generation click chemistry. Reversible 9-bp hybridization between the substrate-side binder and the ssDNA target results in transient particle binding. In the presence of target, particles can bind to the surface due to target-induced sandwich binding, switching from an unbound state (left) to a single- or double-bound state (right). [Figure 10] The results are shown for single-stranded DNA targets at concentrations of 1 pM, 10 pM, and 100 pM, which were sequentially added to the sensor to perform a DNA sandwich assay. The particle positions were tracked at a frame rate of 60 Hz over a 10-minute period. The diffusion coefficient histograms for the particle ensembles were plotted for each concentration, showing the unbound and bound populations as a function of target concentration. [Figure 11] An example of the evolution of single particle trajectories and the corresponding diffusion coefficients is shown. A single-stranded DNA target at a concentration of 10 pM was added to perform the DNA sandwich assay described in Figure 9. The particle positions were tracked over a 10 min period, allowing the particle trajectories (inset graph) to be reconstructed. The diffusion coefficients of all particles are calculated as a function of time, and binding / unbinding events are detected for all particles in the field of view. [Figure 12] Examples of single particle trajectories and the corresponding evolution of diffusion coefficients are shown. A single-stranded DNA target at a concentration of 50 pM was added to the system shown in Figure 9, followed by a 5-minute measurement. In these examples, the particles primarily switched between the single- and double-bound states. Time traces with two binding states are shown, corresponding to the time spans marked by different grayscale colors in the inset. The particles exhibit a pancake-like motion pattern in the single-bound state and a striped or dot-like motion pattern in the double-bound state. [Figure 13]This paper demonstrates the basic principle of a monitoring biosensor based on measuring the free, long-range diffusional motion of biofunctionalized particles with reversible molecular binding to a substrate. Figure 13A shows microparticles functionalized with particle-side binders. The particles diffuse near a substrate functionalized with substrate-side binders. The binders have specific affinity for the target molecule. A target-induced sandwich complex is reversibly formed, switching the particles between unbound and bound states. The particles exhibit free Brownian motion in the unbound state and confined Brownian motion in the bound state. The right panel of Figure 13A shows a microscopic image of approximately 500 particles within a field of view of approximately 500 μm × 500 μm. The inset shows the reconstructed in-plane trajectories of a subset of particles (n = approximately 25) tracked for 300 seconds. Figure 13B shows experimental data for a sandwich system with an oligonucleotide binder and a target. The left column of Figure 13B shows the trajectories of a single particle in the absence (top) and presence (bottom) of a target molecule in solution. The black dots in the bottom panel indicate the bound state induced by target-induced sandwich binding. The right column of Figure 13B shows the diffusion parameter D calculated as a function of time based on the in-plane displacement derived from particle trajectories. In the absence of analyte (top), particles typically exhibit free Brownian motion. In the presence of analyte (bottom), particles transition from the unbound (gray) state to the bound (black) state. The resulting state transition is indicated by a binary step function (top line). Figure 13C shows the distribution of measured D for approximately 500 particles, showing the populations of unbound (gray) and bound (black) states depending on the target concentration. [Figure 14]Figure 14A shows the mobility time traces and state lifetimes for particles with diameters of 1 μm and 2.8 μm. Figure 14A shows the diffusion coefficient. Figure 14D shows values ​​measured over a 5-minute period, representing the unbound (gray) and bound (black) states. Figure 14B shows the distribution of D derived from a single particle trace in panel A, illustrating the difference between 1 μm and 2.8 μm particles. Figure 14C shows the D distribution for several hundred particles. Figure 14D shows the distribution of unbound state lifetimes plotted as survival curves for 1 μm and 2.8 μm particles with similar biofunctionalization and target concentrations. Larger particles exhibit shorter unbound state lifetimes than smaller particles under comparable conditions. The inset shows the same data on a lin-lin scale. Figure 14E shows the survival plot as in panel D, but now for bound state lifetimes. The curve segments are attributed to short-lived monovalent and long-lived multivalent binding. [Figure 15]Figure 15A shows a DNA-based sandwich assay using 2.8 μm particles. Characteristic unbound lifetime survival curves, showing their dependence on target concentration, are shown. As the DNA sandwich target concentration increases, the survival curve becomes steeper (black arrows), reflecting shorter times between binding events. Figure 15B shows the characteristic unbound lifetimes (circles) depending on target concentration over the 30-500 pM range, scaling as approximately [T] -1.6 ± 0.1. The characteristic bound lifetimes (triangles) are independent of target concentration, averaging 13 ± 2 seconds (dashed line). Lifetimes for the blank and 15 pM target samples are not reported because the fitted lifetimes are much longer than the measurement time due to low background. Error bars represent the standard deviation of the lifetime fitting and are typically smaller than the symbol size. The inset shows a neutravidin substrate functionalized with an ssDNA binder combined with 2.8 μm particles functionalized with different ssDNA binders. The ssDNA target strand is also shown. Figure 15C shows a dose-response curve of activity fitted with the Hill equation, with an EC50 of 65 ± 4 pM. The inset shows the response in the bound fraction, with an EC50 of 240 ± 40 pM. The dashed lines indicate the 95% confidence interval for the Hill equation fit. Figure 15D shows continuous monitoring of the sensor's target concentration and reversibility (fitted with an exponential decay function, solid lines). The bottom panel of Figure 15D shows sandwich target concentrations applied stepwise over time, followed by a buffer wash. The top panel of Figure 15D shows that the switching activity measured over time increases with increasing target concentration, demonstrating reversibility within 90 minutes. Sensor function is retained after a buffer wash step. [Figure 16]Figure 16A shows the response of a sensor with 1 μm particles to target concentration for an ssDNA competition assay in PBS and undiluted filtered plasma. The 1 μm particles were functionalized with a particle-side binder via biotin-streptavidin interaction and DNA hybridization. The DBCO-tagged substrate-side binder was coupled to a PLL-g-PEG polymer via an incorporated azide group using second-generation click chemistry. Reversible 9-bp hybridization between the substrate-side binder (which also functions as an ssDNA analog) and the particle-side binder results in transient particle binding. In the presence of the 11-nt target, the binding region on the particle-side binder is blocked, causing a decrease in the binding fraction and a decrease in switching events. Figure 16A shows the sensor response curve, i.e., the binding fraction and switching activity as a function of target concentration, fitted with the Hill equation. The black and gray curves represent two sequentially measured dose-response curves with decreasing concentration series, demonstrating the reversibility of the sensor and its suitability for monitoring applications. Figure 16B shows the characteristic unbound lifetimes as a function of target concentration in the range of 10-2000 nM. Figure 16C shows the switching activity measured for a ssDNA target in 50 kDa spin-filtered bovine plasma. Figure 16D shows the characteristic unbound and bound lifetimes measured in filtered bovine plasma. [Figure 17]A reversible sensor for detecting the sepsis biomarker procalcitonin (PCT) was demonstrated using an antibody sandwich immunoassay. Data are shown for two sensor devices. A glass substrate was functionalized with 100 nM capture antibody (c-Ab) by physical adsorption, followed by blocking with 1% BSA in PBS (blocking buffer). Streptavidin-coated 2.8 μm Dynabeads were functionalized with 100 nM biotinylated detection antibody (d-Ab), blocked with 100 μM biotinylated PEG (1 kDa), and blocked with blocking buffer. The d-Ab-functionalized microparticles were diluted to 66 μg / mL in PBS containing 0.1% BSA (assay buffer) and injected over the c-Ab-functionalized sensor surface. The analyte PCT was spiked into the assay buffer, and 30 μL of the solution was injected into the sensor flow chamber. Each injection was performed with flow reversal, i.e., alternate feeding at the inlet or outlet, to minimize particle loss in the active field of the sensor. Washing was performed with the same assay buffer injections as for PCT measurements to reach a baseline bound particle fraction (open symbols) a minimum of three times. Particle movement was tracked for 10 min at 60 Hz under bright-field illumination. The data clearly demonstrate the sensor's monitoring function, i.e., the sensor response to PCT concentration and the reversibility of the sensor. DETAILED DESCRIPTION OF THE INVENTION

[0042] Particle size definition The diffusivity of an unbound spherical particle of radius R is given by the Stokes-Einstein relation:

number

[0043] However, it is further noted that it is more difficult to accurately track small particles than large particles because small particles diffuse faster. Furthermore, large particles give more signal, e.g., the optical signal of a small particle is smaller than that of a large particle because large particles scatter or generate more photons.

[0044] The distance between the particle and the surface in the biosensor of the present invention may depend on the size of the particle.

[0045] We assume that particles are attracted towards the surface with a force F. The force can be time and space dependent, but here we assume that the force is constant (for simplicity). We now assume that due to thermal energy, all particles are distributed to different particle positions. Due to thermal energy, particles have a characteristic decay length (which can be seen similar to a pressure height) in the near-surface region:

number

[0046] In the case of gravity, the characteristic decay length of the particle is given by the buoyancy force. We have assumed (for simplicity) a spherical particle with radius R and an effective mass density difference Δρ between the particle and the solution. Then:

number

[0047] Equation 3 shows that the height spread of small particles is much larger than that of large particles. A large height spread increases the average distance between the particle and the surface, which is unfavorable for the collision or encounter rate between the particle and the surface, and therefore hinders the effective association rate between the particle and the surface.

[0048] Note that the mass density difference Δρ can be positive (i.e., the particle is heavier than the solution and the particle "sinks" toward the biosensing surface) or negative (i.e., the particle is lighter than the solution and the particle "floats" toward the biosensing surface).

[0049] Alternatively or additionally, the particles may be maintained near the surface by mechanical means, for example, by a second surface that limits the height space in which the particles can reside or limits the accessible distance range between the particles and the first surface, which can act as a means to keep the particles close to the first surface and prevent them from moving too far away from the first surface. In another embodiment, the second surface may be porous such that the analyte and / or fluid can permeate the second surface or penetrate through the second surface into and / or leach from the particle-containing region.

[0050] In another embodiment, the first surface may be porous such that the analyte and / or fluid can permeate or penetrate through the first surface into and / or leach from the particle-containing region.

[0051] Large particles can provide a small height spread and a small effective distance between the particle and the surface (see above). However, a small height spread and a small effective distance can also hinder the reversibility of biomolecular interactions and reduce the dissociation rate. Large particles can provide steric hindrance, slowing down the association and dissociation processes, i.e., the switching of the biosensor device system of the present invention from its first state to its second state and vice versa. Furthermore, large particles can provide nonspecific interactions between the particle and the surface, including irreversible adhesion, even when the particle and the surface are coated with blocking and antifouling coatings.

[0052] Biosensor device using 1 μm diameter particles Biosensor devices containing particles with diameters of either 1 μm or 2.8 μm were prepared. Two types of biosensor devices were prepared using streptavidin-coated 1 μm particles (Dynabeads MyOne C1). 10 μM particle binder biotin-oligo (SEQ ID NO: 1) was coupled to the particles via streptavidin. The remaining particles were blocked using 100 μM 1 kDa PEG-biotin and 1% BSA.

[0053] The surface (Biosensor Device A) was prepared using a glass substrate containing 100 μg / mL neutravidin (physisorbed) and 500 nM surface biotin-oligo (SEQ ID NO: 4) coupled to the surface via neutravidin, with a detection oligo (SEQ ID NO: 3) coupled to the surface via biotin-oligo. The remainder of the surface was blocked with 100 μM 1 kDa PEG-biotin and 1% BSA.

[0054] Alternatively, another surface (biosensor device B) was prepared using PLL-g-PEG and click-coupled biotin-oligo on a glass substrate.

[0055] A flow cell cartridge with a measurement chamber was constructed using a double-sided adhesive layer and a top plate with fluid inlets and outlets. Data were collected by exchanging fluids within the flow cell, i.e., by sequentially inserting solutions with different analyte concentrations. Fluids were inserted manually using a pipette. Experimental flow rates were typically around 1-300 microliters per minute.

[0056] The analyte having SEQ ID NO:2 was used as the target.

[0057] [Table 1]

[0058] Results of DNA sandwich and competition assays The data from biosensor device A show that the diffusion coefficient histogram and measured state lifetimes depend on the analyte concentration applied to the flow cell. Reversible switching between associated and dissociated states was observed, allowing for the extraction of state lifetimes. The state lifetimes indicate short-lived and long-lived states, which can be attributed to different types of interactions, e.g., different valencies.

[0059] An example of biosensor device B shows measured diffusion coefficient histograms as a function of analyte concentration applied to the flow cell, with kinetic traces at a 10 pM concentration (free, single-bound, and multiple-bound states visible) and a 50 pM concentration (single-bound and multiple-bound states visible).

[0060] Insights provided by the biosensor of the present invention The data from the experiment show the following: - Particle tracking is possible with sufficient accuracy over a sufficiently long period of time, with unambiguous detection of the particle association and dissociation states in the biosensor device - statistical analysis of the associated and unassociated state lifetime distributions shows a dependence on the target concentration (picomolar range) with high sensitivity, and - The distribution of associated and unassociated state lifetimes shows multiple characteristic lifetimes (see multi-exponential fitting) and corresponding population fractions for transitions between different states (e.g., unbound, monovalently bound, multivalently bound), all of which exhibit target concentration dependence.

[0061] Observation of different states (unbound, monovalently bound, multivalently bound, etc.) allows the measurement of different transition rates and state lifetimes, which depend on the amount of target captured on the particle and surface, and therefore on the concentration of target in solution. For example, if a particle is observed in a monovalently bound state or single-molecule bound, additional bonds may form. This yields lifetimes and transition rates corresponding to the formation of the first and additional bonds, which are concentration-dependent but of different magnitudes. This results in multiple parameters that can be extracted and used to improve biosensing performance.

[0062] Important biosensing performance aspects of a biosensor are, for example, sensitivity, specificity, speed, reversibility, precision, accuracy, dynamic range, robustness, stability, and multiplexing.

[0063] Furthermore, lifetimes measured for different states (e.g., single and multiple binding states) provide information about the affinity of the molecule, e.g., association rate, dissociation rate and equilibrium binding constant, which can be used to characterize the properties of the molecule.

[0064] Furthermore, we observed that after filling the flow cell and starting the measurement, fluids could be exchanged within the flow cell with minimal particle disturbance. Therefore, particle mobility assays without fixed tethers can be used for continuous biomarker monitoring. Due to the reversible interaction, increases and decreases in analyte concentration can be followed.

[0065] Additionally, changing the direction of flow within the flow cell can help compensate for displacement and minimize the net distance displaced by particles, which minimizes particle loss and allows for long measurement sequences and measurements over long periods of time.

[0066] The preferred distance between the particle and the surface in the unbound state is in the range of 5 nm to 10 μm. The lower limit (5 nm) is determined by the fact that molecules and reversible biomolecular interactions, which typically operate on length scales of a few nanometers, are used, and sufficient space is required between the particle and the surface so that the unbound state can be achieved. The upper limit (10 μm) is determined by the fact that a sufficiently high collision velocity between the particle and the surface is required to achieve an effective association rate so that a sufficient transition from the unbound state to the bound state can be observed.

[0067] Advantages of assays without fixed tethers (versus assays with fixed tethers): - No tethering is required, resulting in fewer reagents and processing steps in chemistry and sensor fabrication; -Without a fixed tether, the sensor is not dependent on tether stability or subject to tether degradation. - the absence of fixed tethers means fewer molecular components and therefore fewer physicochemical constraints, resulting in a larger window of physicochemical and (bio)chemical manipulation, e.g., potentially being able to use a wider variety of buffers and potentially being able to apply a wider temperature range, Sensors without fixed tethers are easier to prepare, allowing assay development, screening of reaction and preparation conditions, and technology development to proceed more quickly. The technical knowledge gained can then be applied to the development of sensors with fixed tethers. - Fewer particles are required for sensor preparation (the tethering process is usually less efficient), - Because the particle has rotational and diffusive degrees of freedom, interactions can occur on all sides of the particle (with a fixed tether, the interaction area is limited to the area around the tether attachment point), which can improve dynamics and sensitivity. Furthermore, this can reduce variability and increase precision due to a larger interaction area per particle (less sensitivity to physical and chemical inhomogeneities on the particle). - Because the particles have translational and diffusive degrees of freedom, associations can be detected over a large surface area (with a fixed tether, the interaction area is restricted to the area around the tether attachment point), which can improve dynamics and sensitivity and reduce variability; The distance between the particle and the surface can be adjusted over a wide range, so that even large analytes, such as nanoparticles, extracellular vesicles, exosomes, nanosomes, liposomes, virus particles, cells, cell fragments, supramolecular objects, protein aggregates can be measured (short fixed tethers may sterically hinder the capture of large analytes between the particle and the surface), Due to the large displacement of the particles, the non-associated state can be easily detected. The sensor can be prepared with particles in a dry state (e.g., in a dissolving matrix) so that it can be used directly by adding a fluid to activate the sensor (this is more complicated in the case of fixed tethers), and By supplying a solution containing particles, new particles can be added to the sensing chamber, which can improve, for example, the cartridge measurement lifetime (see below).

[0068] Other aspects of the invention The biosensor of the present invention comprises multiple components, such as components for sampling an analyte from a system of interest (e.g., a biological system, an environmental system (e.g., a river, pond, ocean, lake, water source), a channel, a pipe, a pool, a well, an exhaust, a process, a reactor, a fermenter, a flow, an organism, a reservoir, a patient, an animal, an organoid), components for pre-treating the sample (e.g., diluting, filtering, heating, enzymatic treatment, separation), components for directing the sample to sensing particles, components for illuminating the particles, components for collecting radiation from the particles, components for imaging the particles, components for determining spatial coordinate parameters of the particles at different times, components for determining displacement or translation or rotation or motion parameters of the particles, components for determining the state and binding of the particles in a time trace, and components for determining the state and binding of the particles in a time trace. The system may include components for determining unbound events, components for processing histograms and distributions of parameters, components for converting processed parameters (e.g., amplitude, state, diffusivity, diffusion constant, lifetime, velocity, population of distribution, fractional occupancy, switching activity, event frequency, time delay) into analytical parameters (e.g., concentration, precision, accuracy, time profile), components for converting analytical parameters into control actions (e.g., warning signals or closed-loop control parameters), components for controlling different components within the system (e.g., a computer with software), or components for communicating with external components (e.g., a larger control system, a database, an internet system, an information system, or a cloud system).

[0069] The biosensor of the present invention can include a reader system (e.g., optical components, components for data and signal processing, components for interface and data communication), a fluidic system (e.g., a method for moving fluids or particles, a pump, a method for applying negative or overpressure, a method for providing dilution, a method for providing mixing, a vent, a tube, a valve, a filter, a switch, a flow sensor, a pressure sensor, a gas sensor, a gas handling method, a degassing unit, a flow regulator, a pressure regulator), or a cartridge or another container device (e.g., an opening, a connector, an inlet, an outlet, a well, a channel, a measurement surface, a measurement chamber, an alignment mark, an identification mark, an ID tag). The system can have a container (e.g., a waste reservoir) for collecting reagents (e.g., buffers, particles, pretreatment reagents) or fluids. The sensor system can include wet or dry reagents (e.g., dried or lyophilized).

[0070] In another embodiment, several fluid, particle, molecular, or analyte transport architectures can be used, such as in-plane transport, out-of-plane transport, cross-flow transport, convection, advection, and diffusion. In another embodiment of the sensor device, the sensor particles can be positioned near a first surface, and the fluid, molecular, or analyte transport can occur in different directions relative to the surface, such as along the surface and / or perpendicular to the surface, including transport through the surface. In another embodiment, the particles can be positioned between a first surface and a second surface, and the transport of fluids, molecules, or analytes can occur in different directions, such as along or through different surfaces. The surface can be biofunctionalized to achieve binding between the particles and the surface.

[0071] Cartridges and other components can be fabricated by patterning techniques (e.g., lithography, contact printing, microcontact printing, non-contact printing, self-assembly), additive manufacturing (e.g., 3D printing), bonding (e.g., gluing, welding, adhesives, adhesive tape), assembly, lamination, automated placement, molding, overmolding, drop casting, curing (e.g., optical, thermal). Other possible fabrication techniques are, for example, biopatterning, biodeposition, bioconjugation, physical adsorption, drying, lyophilization, irradiation, sterilization, packaging, and sealing.

[0072] Conditioning the sample or sample stream by chemical, biochemical, or physical means can improve the analytical performance of the sensor, for example, by stabilizing the pH, temperature, solution mass density (which is related, for example, to Δρ in Equation 3), solution composition (e.g., absence of interfering molecules or cellular aggregates), etc.

[0073] Particle detection and tracking may include radiation, waves, electromagnetic principles, acoustics, scattering, fluorescence, absorbance, interference, plasmonic sensing, spectroscopic sensing, imaging, etc. Detection may allow reliable tracking of individual particles.

[0074] Alternatively, if an optical detection method is used, the cartridge and optical components may comprise an optically transparent material, such as glass or a polymer.

[0075] In another aspect, the height tolerance of the method for tracking coordinate parameters (e.g., depth of focus in the case of some optical tracking methods) preferably accommodates particle height variations (see, e.g., Equation 2), so that a reliable tracking algorithm can be developed, and thus the probability of losing particle tracking due to height variations is tolerable relative to other error sources.

[0076] For example, if the amount of time a particle can be tracked is longer than the time required to determine whether the particle is in one state or another, the state of the particle can be determined with precision and / or accuracy. For example, if the amount of time a particle can be tracked is longer than the time required to determine effective spatial coordinate parameters or motion parameters, the effective spatial coordinate parameters or motion parameters can be determined with precision and / or accuracy. For example, if a sufficiently high fraction of particles interacting with a surface are tracked, the bound fraction, unbound fraction, and / or bound-to-unbound ratio can be determined with precision and / or accuracy. For example, if the amount of time a particle can be tracked is longer than the characteristic state lifetime of the particle, the characteristic state lifetime can be determined with precision and / or accuracy.

[0077] The biosensors of the present invention can be prepared for immediate use, rapid use, or plug-and-play, for example, by incorporating particles stored in a fluid or in a dissolvable matrix that is dispersed and activated upon wetting for sensing function within a measurement chamber.

[0078] The biosensors of the present invention can be used with a variety of binding agents, eg, molecules, molecular constructs, and materials, such as oligonucleotides, proteins, peptides, polymers, aptamers, small molecules, sugars, molecularly imprinted polymers, and the like.

[0079] The associated and dissociated state lifetimes in the system can be tuned, for example, by the choice of binder, binder density, blocking method, buffer conditions, and the like.

[0080] If the average tracking time of an individual particle is longer than the average associated and / or dissociated lifetime of the particle, multiple (un)associated events can be measured per particle, which is advantageous for the accuracy of statistics and derived parameters.

[0081] Biosensors of the invention can include components and methods for dissociating or removing particles from the sensor, for example, by applying fluid-mechanical drag (e.g., flow pulses), interfacial tension (e.g., gas / liquid interfaces, bubbles), field forces (e.g., magnetic fields, acoustic forces, optical fields), thermal excitation, or other directed or random forces to the particles or fluid. Biosensors of the invention can also include components or methods for supplying or adding particles, for example, by flowing a fluid containing dispersed particles into the measurement chamber or by other forces on the particles or fluid. Removal and / or addition can be useful for optimizing the sensor or for resetting, regenerating, restarting, or refreshing the sensor.

[0082] Removing particles can be useful when particles are no longer suitable for sensing, e.g., when they become inactive, unresponsive, static, or saturated. Adding or replacing particles can be useful to provide particles with better or different sensing properties, e.g., for sequentially measuring different analytes, or for sequentially sensing the same analyte at different time points (particularly relevant when relaxation times are long), or for sensing the same analyte with particles having different response properties (e.g., different sensitivity or specificity).

[0083] Biosensors of the invention can have mixed sensing particles, eg, particles with and without fixed tethers, or particles with different optical and / or sensing properties (eg, multiplexing).

[0084] The biosensors of the present invention can be used to measure affinity parameters and distributions of affinity parameters, distributions of molecules and / or distributions of particle-surface combinations.

[0085] The biosensors of the present invention can be used for continuous monitoring, intermittent testing, as well as endpoint measurements, eg, for point-of-use or use in a laboratory setting. The biosensors of the present invention can be used, for example, in industrial process monitoring, life science applications, medical applications, fermentation, bioreactors, patient care, clinical trials, pharmaceutical applications, environmental monitoring, in situ testing, home environment monitoring, extraterrestrial testing, air quality monitoring, vapor testing, breath fluid testing, water monitoring, chemical monitoring, closed loop control, real time monitoring, early warning systems, and the like.

[0086] More Information In further embodiments of the device or method of the present invention, the biosensor may not be in direct contact with the system of interest, or may be in direct contact with the system of interest. Alternatively, the biosensor may be embedded, integrated, or implanted in the system of interest. The biosensor may be located remotely from the system of interest. However, the biosensor may also be located near the system of interest, on top of the system, wirelessly integrated, or otherwise. The sample may be placed in a container and then transported to the biosensing system (sometimes referred to as at-line or offline operation), the sample may be collected and automatically transported to the biosensing system (sometimes referred to as online operation), or the biosensing system may be fully integrated into the system of interest (sometimes referred to as in-line or bypass operation).

[0087] In further embodiments of the invention, the device or method may be connected to or incorporated into an industrial system or process, a fermenter, a bioreactor, an on-body device, a catheter, an in-body device, a wearable device, or an internal device.

[0088] In a biosensing system with monitoring capabilities, time-dependent samples can be taken, measurement data can be recorded, and a temporal profile of analyte concentration as a function of time can be established. The biosensor can also be configured to receive a series of samples (from the same or different sources), which are measured sequentially on the biosensor, resulting in time-dependent data for the different samples provided to the biosensor.

[0089] In further embodiments of the invention, the device or method can be combined with methods or device modules for sample or analyte pre-treatment, such as adding reagents, diluting, filtering, extracting, concentrating, purifying, separating, amplifying, changing buffer conditions, stabilizing, (de)aggregating, or removing, modifying or adding chemical groups or biochemical domains or residues or moieties.

[0090] In further embodiments of the invention, the device or method may be combined with method or device modules for optimizing or controlling operation, for example, temperature, humidity, pressure, light conditions, vibration conditions, sound conditions, sterility, hygiene, ingress protection, cleaning, part replacement, easy maintenance, calibration, etc.

Claims

1. A biosensor device capable of sensing an analyte continuously, repeatedly, or intermittently over a period of time using particle motion, the biosensor device having a functionalized surface and particles, the biosensor device has a first state in which the particles are associated with the surface and a second state in which the particles are not associated with the surface; switching between the first state and the second state is dependent on the presence, absence and / or concentration of the analyte; whereby the motional properties of the particles are changeable in response to the presence, absence and / or concentration of the analyte, thereby enabling sensing of the analyte by measuring changes in spatial coordinate parameters of the particles relative to the surface; the properties of the particle and the surface are selected such that in the second state the particle is within proximity of the surface such that the biosensor device can measure a change in a spatial coordinate parameter of the particle relative to the surface; the particles are not conjugated to the surface; Biosensor devices.

2. the first state in which the particle is associated with the surface comprises a first association state and a second association state; the first association state comprises a single molecular bond between the particle and the surface; the second association state comprises two or more single molecular bonds between the particle and the surface; The biosensor device of claim 1 .

3. comprising at least 10 particles, The biosensor device according to claim 1 or 2.

4. 415 x 415 μm ２ The density ranges from a few particles to several thousand particles. The biosensor device according to any one of claims 1 to 3.

5. an optical system having a diffraction limit, the optical system including particles separated from nearest particles by at least the diffraction limit of the optical system; The biosensor device according to any one of claims 1 to 4.

6. conducting binding assays, competitive assays, displacement assays, sandwich assays, enzymatic assays, assays involving target and / or signal amplification, multi-step assays, or assays involving molecular cascades; The biosensor device according to any one of claims 1 to 5.

7. the particles are functionalized with a first moiety attached to the particles; or the surface is functionalized with a second moiety attached to the surface; the moiety has a binding affinity for the analyte; The biosensor device according to any one of claims 1 to 6.

8. the particles are functionalized with a first moiety attached to the particles; and the surface is functionalized with a second moiety attached to the surface; the moieties have binding affinity for each other depending on the presence, absence or concentration of the analyte; The biosensor device according to any one of claims 1 to 6.

9. the dissociation rate constants of the analyte and the first moiety differ by at least three-fold relative to the analyte and the second moiety; or the dissociation rate constants of the first and second moieties differ by at least three-fold for the analyte and the first moiety and / or for the analyte and the second moiety; The biosensor device according to claim 7 or 8.

10. 10 ０ ~10 ８ Part / μm ２ having a density of the part in the range of The biosensor device according to any one of claims 7 to 9.

11. the first moiety or the second moiety is a protein, an antibody, a fragment thereof, a recombinant protein, a peptide, a carbohydrate, a saccharide, a molecularly imprinted polymer, a small molecule, a nucleic acid, a DNA molecule, a PNA molecule, an aptamer, a nanobody, a multivalent binding agent, or a combination thereof; The biosensor device according to any one of claims 7 to 10.

12. Use of a biosensor device according to any one of claims 1 to 11 in a method for performing multiplexing.

13. 12. Use of the biosensor device of any one of claims 1 to 11 in combination with a system for sensing or monitoring, comprising an endoscope, a tube, a needle, a fiber, a catheter, a patch, a disposable probe, a flow cell, or a disposable cartridge.

14. 12. The biosensor device of any one of claims 1 to 11 for use in in vivo, ex vivo or in vitro biosensing or for monitoring assays using living cells, tissues or organs in in vitro diagnostic testing, point of care testing, environmental testing, food testing, process monitoring, process control, forensic, biological, biomedical and pharmaceutical research.

15. 1. A method for sensing an analyte using particle motion, comprising: a) contacting the matrix containing the analyte with the biosensor device of any one of claims 1 to 11, and b) detecting motional properties of said particles that vary in response to the presence, absence and / or concentration of said analyte; the motion characteristics include spatial coordinate parameters of the particle relative to the surface; method.

16. The particles are configured to switch from said first state to said second state in a mean effective dissociation time; arranged to switch from said second state to said first state in an average effective engagement time; step b) detecting the particle motion characteristics is carried out for a period of time longer than the mean effective dissociation time and / or the mean effective association time; 16. The method of claim 15.

17. In step b), the direction of flow of the matrix containing the analyte is changed continuously or intermittently.

17. The method of claim 15 or 16.

18. The flow changes are subject to random flow direction changes or reverse flow direction changes; 18. The method of claim 17.

19. The method of claim 18, wherein the distance between the particle and the surface in the second state is within a range of 5 nm to 10 μm. The biosensor device of claim 1 .

20. A method for producing a granular material comprising: The biosensor device according to claim 1 or 2.

21. The dissociation rate constants of the analyte and the first portion differ by at least a factor of 5 relative to the analyte and the second portion; or the dissociation rate constants of the first and second moieties differ by at least 5-fold for the analyte and the first moiety and / or for the analyte and the second moiety; The biosensor device according to claim 7 or 8.

22. The method of claim 21, wherein the first or second moiety is a binding molecule for glucose, an electrolyte, a metabolite, a small molecule, a lipid, a carbohydrate, a peptide, a hormone, a drug, a drug metabolite, a protein, an oligonucleotide, DNA, RNA, a nanoparticle, an extracellular vesicle, an exosome, a nanosome, a liposome, a virus particle, a cell, a cell fragment, a supramolecular object, or a protein aggregate. The biosensor device according to any one of claims 7 to 10.

23. Use of a biosensor device described in any one of claims 1 to 11 in a method for performing analyte multiplexing, spatial multiplexing, spectroscopic multiplexing, or probe function multiplexing.

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