Biosensor using particle motion

Abstract

The invention relates to a biosensor device for sensing an analyte over a certain period of time using particle motion, the biosensor device having a surface and particles, wherein the particles and / or the surface are functionalized, and wherein 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, and wherein the transition between the first and second state depends on the presence, absence and / or concentration of the analyte, whereby the motion characteristics of the particles change depending on the presence, absence and / or concentration of the analyte, and wherein the properties of the particles and the surface are chosen such that in the second state the particles are in the vicinity of the surface such that the biosensor is able to measure changes in the spatial coordinate parameters of the particles relative to the surface, wherein the particles are not conjugated to the surface.

Description

TECHNICAL FIELD

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

[0002] Biosensor devices for chemical or biochemical labeling are typically developed for in vitro diagnostics, where a sample (e.g. blood, saliva, urine, mucus, sweat or cerebrospinal fluid) is collected and transferred to an artificial device (e.g. disposable plastic) outside the living organism. In such bio-sensing assays, a wide range of sample pre-treatment steps (e.g. separation or dilution steps) can be applied and a variety of reagents can be introduced in the assay (e.g. for target amplification, signal amplification or washing steps). Examples of in vitro bio-sensing assays are: immunoassays, nucleic acid tests, tests for electrolytes and metabolites, electrochemical assays, enzyme activity assays, cell-based assays, etc. For a complete overview, refer to Tietz textbook of clinical chemistry and molecular diagnostics (Connell, 5thedition, 2012).

[0003] In in vivo bio-sensing, at least a part of the sensor system remains connected to or inserted into the living organism, e.g. the human body, e.g. on, in, 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 bio-sensing puts high demands on biocompatibility (e.g. inflammation processes should be minimized) and the sensor system should reliably operate within the complex environment of the living organism. For monitoring applications, the system should be able to perform more than one measurement over time and the system should be robust and easy to handle.

[0004] One known application of in vivo biochemical sensing is continuous glucose monitoring (CGM). Commercial 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 not as versatile as affinity-based sensing. Commercial systems for in vivo glucose monitoring are available from, for example, Dexcom and Medtronic.

[0005] There are many applications in the field of sensing and monitoring. Biological systems, such as cells, multicellular systems, organs, organisms or other systems and materials based on or containing biomolecules or cells, exhibit dynamics at the most fundamental level driven by time-dependent changes of biological organic molecules such as, for example, small molecules, metabolites, hormones, proteins or nucleic acids. For a variety of applications, it would be highly valuable to be able to monitor specific molecules that reflect the dynamics exactly, so that actions can be taken in time and changes can be managed. Sensing technologies for measuring and monitoring biological molecules would allow to study the dynamic changes of biological systems and control such systems based on the measured responses, for example in the fields of health care, bioengineering and industrial processing. Sensors can be used to measure pH, electrolytes and metabolites continuously, but not yet biological molecules at low concentrations.

[0006] One known technology for measuring biological molecules and biological molecule interactions is tethered particle motion (TPM). TPM technology is based on the measurement of the motion of particles tethered to a surface. Laurens et al. (Dissecting protein-induced DNA looping dynamics in real time; Nucleic acids research 37 (16), 2009: pp. 5454-5464) describe one example of such a system, in which TPM experiments report on proteins bound to DNA tethers in order to reveal how proteins change the DNA conformation. In such studies, measures are taken to avoid particles binding to the surface not via the tether, because particles bound to the surface in another way than via the tether do 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 the particles attached by the tethers changes depending on 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. There are also techniques for detecting an analyte by measuring the kinematic properties of functionalized particles tethered to a surface depending on the presence of the analyte. In these techniques, it is important to avoid binding of the particles to the surface, as steric hindrance would interfere with the sensitivity affected by the analyte.

[0008] Even more biosensors based on TPM technology with functionalized particles and / or functionalized surfaces have been described, for example, in the international patent application published under WO 2016 / 096901 Al. SUMMARY

[0009] In view of the biosensors described in the art, the inventors have developed a novel biosensor device suitable for sensing an analyte continuously, repeatedly or intermittently over a certain period of time using the motion of particles. The present invention provides for this a biosensor device having a surface and particles, wherein the particles and / or the surface are functionalized, and wherein:

[0010] - 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; and

[0011] - the transition between the first and second state depends on the presence, absence and / or concentration of the analyte,

[0012] from which the kinematic properties of the particles are changeable depending on the presence, absence and / or concentration of the analyte, allowing the analyte to be sensed by measuring the change in the spatial coordinate parameters of the particles relative to the surface. It has been found that if the properties of the particles and the surface are chosen such that in the second state the particles are in the vicinity of the surface, such that the biosensor is still able to measure the change in the spatial coordinate parameters of the particles relative to the surface. The phrase "in the vicinity of the surface" can refer to a distance between the particles and the surface in the second state, wherein the biosensor is still able to measure the change in the spatial coordinate parameters of the particles relative to the surface. It is noted that such a distance between the particles and the surface is not limited to any distance, it is noted that a larger distance between the particles and the surface results in a less efficient biosensor compared to a biosensor in which the distance between the particles and the surface is smaller. Preferably, the distance between the particles and the surface in the second state is at least 5 nm, more preferably in the range of 5 nm to 100 pm, more preferably in the range of 5 nm to 10 pm. It has been found that it is no longer necessary to conjugate the particles to the surface. In other words, the present invention provides a non-tethered biosensor device suitable for a method for continuously sensing an analyte.

[0013] It has been found that, although the particles are not attached to a surface, for example using tethering heads, the biosensor device of the present invention is capable of continuous molecular biosensing without a fixed tether between the particles and the surface. That is, the particles remain adjacent to the surface, for example due to field forces, such as gravitational fields. The particles of the biosensor device of the present invention exhibit Brownian motion, and the motion changes as the particles transition between associated and unassociated states (also referred to as "dissociated states"). The particle motion behavior and the lifetime of the associated / dissociated states depend on the concentration of the target analyte (i.e., the analyte) in the solution.

[0014] As used herein, the term "attachment" refers to the covalent attachment of a first molecule to a second molecule. Furthermore, the term "attachment" refers to the connection of one component of a biosensor device to another component of the same device, for example, by crosslinking a particle of the biosensor device to a surface of the biosensor device via, for example, a connector or tether. As used herein, the phrase "particle not attached to surface" refers to a freely moving particle that is not attached to a surface in an unattached state.

[0015] As used herein, the term “biosensing” refers to the use of biosensors to identify, test, characterize, monitor, and otherwise measure analytes.

[0016] As used herein, the term "analyte" refers to a substance that is identified, tested, characterized, monitored, or otherwise measured; an analyte may comprise molecules of a single target species (e.g., glucose) or molecules of multiple target species (e.g., glucose and synthetic deoxyribonucleic acid (DNA)). Examples of analytes include latex beads, lipid vesicles, whole chromosomes, nanoparticles, extracellular vesicles, liposomes, viruses, cells, cell debris, supramolecular bodies, protein aggregates and biomolecules (including proteins and nucleic acids), gaseous molecules (e.g., ethylene), metal or semiconductor colloids and clusters, small molecules in the sub-nanometer to 10 nm size range, metabolites, and other such chemical molecules.

[0017] As used herein, the term "particle" can refer to an object having detectable motion within a fluid or viscoelastic matrix. Fluids or viscoelastic matrices are often simply referred to as fluids. Particles can consist 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 structures (e.g., spherical, rod-shaped, hollow, star-shaped, bubble-shaped, hybrid systems, intramatrix particles, aggregates, regular or irregular). They can have a short axis in the range of 1 nm to 15 μm, more preferably 5 nm to 5 μm, and even more preferably 10 nm to 3 μm.

[0018] As used herein, the term "surface" can refer to an object with respect to which coordinate parameters of a particle, such as position, distance, translation, displacement, angle, orientation, rotation, translational velocity or angular velocity, can be measured. The surface can consist of, for example, organic or inorganic materials or combinations thereof. It can have different shapes (e.g. flat, curved, corrugated) and different internal and external structures (e.g. solid, porous, permeable, layered, flexible, viscoelastic).

[0019] With respect to surfaces suitable for use in the present application, it is noted that the surface can be a support structure, such as a flat surface, a surface with concave or convex structure, a chemically and / or physically patterned surface, a particle, a polymer, a porous structure or a porous matrix. It is emphasized that the surface can also be a three-dimensional structure.

[0020] As used herein, the phrase "properties of the particle and the surface" refers to parameters of the particle, the surface and the fluid which result in a distance between the particle and the surface in the second state, for example, in the range of 5 nm to 10 pm. For example, particle parameters relevant to providing a biosensor of the present application can include the size of the particle and the density of the particle. For example, surface parameters can be the choice of surface material or material type or design with acoustic or magnetic or transport or mechanical properties etc. Furthermore, the phrase "properties of the particle and the surface" includes the cooperation between the particle, the surface and the fluid, i.e. the method of binding the particle to the surface, for example, by weight, by acoustic field, by flow, by mechanical binding etc., and the corresponding properties such as density, temperature, applied field, mechanical design etc.

[0021] As used herein, the term "biosensor" can refer to any suitable sensor used in biochemical tests, biological tests, chemical tests, electrochemical tests etc.

[0022] As used herein, the phrase "associated with the surface" refers to a non-covalent binding or attachment and means, for example, that the particle of the present application is adhered to, bonded to or electrostatically attached to the surface of the biosensor device.

[0023] The biosensor device of the present application can contain various numbers of particles. Preferably, however, the biosensor device of the present application can comprise at least 10 particles, more preferably at least 100 particles. It has been found that by providing a biosensor device comprising more than 10 particles, more preferably more than 100 particles, a robust and reliable biosensing method can be performed. It has further been found that the biosensor device can comprise a density of several particles to several thousand particles in an area of 415 x 415 pm 2 Preferably, the biosensor device can comprise a density of several particles to several thousand particles in an area of 415 x 415 pm 2100 to 100,000 particles in the region, more preferably 500 to 20,000 particles, and even more preferably in 415 × 415 μm 2 The particle density is between 1,000 and 10,000 particles in the region. The total area where the particles are tracked is preferably 10. 0 Up to 10 8 μm 2 , more preferably 10 3 Up to 10 7 μm 2 , more preferably 10 4 Up to 10 6 μm 2 .

[0024] In order to sense the analyte, the biosensor device may include a diffraction-limited optical system, wherein the biosensor device includes a particle that is diffraction-limited to the nearest neighbor particle at least within the optical system.

[0025] The biosensor device of the present invention can perform binding assays, competitive assays, displacement assays, sandwich assays, enzymatic assays, assays utilizing target and / or signal amplification, multi-step assays, or assays utilizing molecular cascades.

[0026] As used herein, the term "functionalization" refers to a state in which inert particles and / or surfaces have been transformed into particles and / or surfaces with specific activities. In particular, particles and / or surfaces can be functionalized using binding sites or binding portions (such as antibodies, aptamers, nanobodies, molecularly imprinted polymers, organic molecules, etc.).

[0027] The particles in a biosensor device can be functionalized with a first portion, wherein the first portion binds to the particle. Instead of having functionalized particles, the biosensor device can include a functionalized surface functionalized with a second portion, wherein the second portion binds to the surface. In the case of using either the first or second portion, where the particle or the surface is functionalized, the portion used has a binding affinity for the analyte. By providing such a system, the steric hindrance of the presence of the analyte causes the particle to move to a second state (i.e., a particle-surface non-associated state), while the absence of the analyte and therefore the absence of any steric hindrance causes the particle to move to a particle-surface associated state (i.e., the first state of the invention).

[0028] As used herein, the term "bonding" refers to a bond or attachment that can be covalent (e.g., through chemical coupling) or non-covalent (e.g., through ionic interactions, hydrophobic interactions, hydrogen bonds, etc.). Covalent bonds can be, for example, esters, ethers, phosphate esters, amides, peptides, imides, carbon-sulfur bonds, carbon-phosphorus bonds, etc. The term "bonding" is broader than and includes terms such as "coupling," "fusion," "association," "connection," and "attachment."

[0029] Alternatively, both the particle and the surface can be functionalized, i.e. to provide a biosensor device of the invention, wherein the particle is functionalized with a first moiety, wherein the first moiety binds to the particle, and wherein the surface is functionalized with a second moiety, wherein the second moiety binds to the surface. In such a configuration of the biosensor device of the invention, the two moieties preferably have a binding affinity to each other depending on the presence, absence or concentration of the analyte. In one aspect, such a biosensor device can provide an analyte biosensing method, wherein in the presence of the analyte, the functionalized particle is in its first state, i.e. associated with the functionalized surface. In another aspect, such a biosensor device can provide an analyte biosensing method, wherein in the absence of the analyte, the functionalized particle is in its first state, i.e. associated with the functionalized surface.

[0030] With regard to the density of the moieties bound to the particle or the surface, it is considered that any density can be suitable to provide a biosensor device suitable for use in a method of biosensing an analyte. Such a surface density can preferably be 10 0 to 10 8 moieties per pm 2 . Preferably, the biosensor device can have a density of moieties in the range of 10 1 to 10 7 moieties per pm 2 , preferably wherein the moieties bound to the particle or the surface have a density in the range of 10 1 to 10 7 moieties per pm 2 , 10 2 to 10 6 moieties per pm 2 , or 10 3 to 10 5 moieties per pm 2 .

[0031] The first moiety or the second moiety can be selected from the group consisting of a protein, an antibody, a fragment thereof, a recombinant protein, a peptide, a carbohydrate, a sugar, 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 moiety or the second moiety is selected from the group consisting of a binding molecule for glucose, an electrolyte, a metabolite, a small molecule, a biologically active substance, a toxin, a lipid, a carbohydrate, a peptide, a hormone, a drug, a drug metabolite, a protein, an oligonucleotide, a DNA, a RNA, a nanoparticle, an extracellular vesicle, an exosome, a nanosome, a liposome, a virion, a cell, a cell fragment, a supramolecular object, or a protein aggregate.

[0032] In another aspect of the application, the present application relates to the use of a biosensor device according to the present application in a method of performing multiplexing, preferably analyte multiplexing, spatial multiplexing (e.g. point multiplexing or chamber multiplexing), spectral multiplexing, probe function multiplexing. Even further, the present application relates to the use of a biosensor device according to the present application as a sensor on, in or as part of a system for sensing or monitoring, which can comprise e.g. an endoscope, a tube, a needle, a fiber, a catheter, a patch, a disposable probe, a wearable device, an insidable device, a flow cell or a disposable cartridge.

[0033] In another aspect of the application, the present application relates to a biosensor device according to the present application for in vivo biosensing, ex vivo biosensing or in vitro biosensing, such as for in vitro diagnostic testing, point-of-care testing, environmental testing, food testing, process monitoring, process control, forensic science, biology, biomedical and pharmaceutical research, or for monitoring assays utilizing living cells, tissues or organs.

[0034] In yet another aspect of the application, the present application relates to a method for sensing an analyte utilizing particle motion, wherein the method comprises the following steps:

[0035] a) contacting a substrate containing an analyte with a biosensor device of the present application; and

[0036] b) detecting a motion characteristic of the particle that changes depending on the presence of the analyte,

[0037] wherein the motion characteristic comprises a spatial coordinate parameter of the particle relative to the surface.

[0038] In view of the method of the present application, it is noted that the particle of the biosensor device of the present application is typically arranged to convert from a first state (i.e. a particle-surface associated state) to a second state (i.e. a particle-surface non-associated state) with an average effective dissociation time. Further, the particle of the biosensor device of the present application is typically arranged to convert from the second state to the first state with an average effective association time.

[0039] Further, it has been found that by controlling the flow of the substrate containing the analyte, the net distance by which the particle can be displaced throughout the biosensor is minimized. Thus, the method of the present application can further comprise the step wherein in step b) the flow direction of the substrate containing the analyte is continuously or intermittently varied. Such variation of the flow can undergo random flow direction variations or undergo reverse flow direction variations.

[0040] As used herein, the terms "average effective dissociation time" and "average effective association time" refer to the average time required for a particle to dissociate from a surface and to associate with a surface, respectively. In other words, the average time required to reach a fully 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 associated state, e.g. with a single molecule bond (monovalent) or with multiple molecule bonds (multivalent)), respectively.

[0041] In view of the average effective dissociation and association times for a particle to reach bound or unbound states with a surface, in a preferred embodiment of the method of the present application, the step b) of detecting the motion characteristic of the particle is performed over a time period longer than the average effective dissociation time and / or the average effective association time. By providing a method wherein the detection of the motion characteristic of the particle is performed over a time period longer than the average effective dissociation time and / or the average effective association time, a robust and reliable method is provided wherein the sensed events with respect to the analyte can be sufficiently measured to achieve good analyte sensing event statistics or to extract state lifetimes and state lifetime distributions.

[0042] The present application describes a biosensor with single molecule resolution. A sensor with single molecule resolution provides a signal with digital characteristics, also referred to as levels, states, transitions, conversions or events. Such digital signals follow the basic laws of Poisson statistics. This means that, for example, the coefficient of variation caused by stochasticity can be proportional to 1 / sqrt(N), where N is the average number of detected events. Therefore, improving the statistics of the detected events reduces the variation and improves the precision.

[0043] In prior art sensors, low concentrations are typically measured by using binding moieties with high affinity and / or with low dissociation rate constants (low k_off). Low dissociation rate constants mean slow unbinding characteristics (long binding state lifetimes of the analyte), which would be disadvantageous if they determined the statistics of the binding events of the particles. In order to obtain good statistics (high number N of detected particle events), the particle state lifetimes should not be too long, otherwise insufficient events are recorded within a given measurement time span.

[0044] In one aspect of the application, the statistics can be improved by having one binding with a relatively low dissociation rate constant (in order to be able to measure low concentrations) and another binding with a relatively high dissociation rate constant (for high N, i.e. good particle event statistics). When the dissociation rate constants differ by a factor of about 3, then the dissociation time of the analyte from the strongest binder (with the lowest dissociation rate constant) is on average three times longer than the dissociation time from the weakest binder (with the highest dissociation rate constant). Due to this time ratio, several particle binding and unbinding events can be observed during the time when the analyte is associated with the strongest binder (e.g. in a sandwich assay), or several particle binding and unbinding events can be suppressed during the time when the analyte is associated with the strongest binder (e.g. in a competition assay). Assuming for example 3 unbinding events and 3 binding events, effectively N=6; this will potentially lower the coefficient of variation by 1 / sqrt(6), which is significantly lower than 1. Thus, due to the ratio between the dissociation rate constants, the variation is significantly lower and the measurement is more precise. Embodiments

[0045] Defining granularity

[0046] The diffusivity of an unbound spherical particle with radius R is given by the Stokes-Einstein relation:

[0047]

[0048] where η is the viscosity of the solution. In view of the Stokes-Einstein relation, it is noted that small particles have a higher diffusivity than large particles. High diffusivity is advantageous for the collision or encounter rate between particles and surfaces.

[0049] However, it is also noted that it is more difficult to track small particles accurately than large particles, because small particles diffuse faster. Furthermore, the optical signal of small particles is lower than that of large particles, because large particles give more signal, e.g. large particles scatter or generate more photons.

[0050] The distance between a particle and a surface in a biosensor of the application can depend on the size of the particle.

[0051] It is assumed that the particles are attracted towards the surface by a force F. The force can be time- and space-dependent; however, here it is assumed that the force is constant (for simplicity). It is assumed here that thermal energy causes each particle to be distributed over different particle positions. Due to thermal energy, the particles have a probability distribution in the near-surface region, with a characteristic decay length (which can be viewed similar to an air pressure height):

[0052]

[0053] where k bis the Boltzmann constant, and T is the temperature. The force F can have multiple origins (e.g. gravimetric, acoustical, magnetic, optical, electrical, fluid-mechanical) and can depend on the size of the particle.

[0054] In the case of gravity, the characteristic decay length of the particle is given by the buoyancy force. Assuming a spherical particle (for simplicity) with radius R and an effective mass density difference between the particle and the solution, Δρ. Then:

[0055]

[0056] where g is the gravitational acceleration. To see the scaling behavior, assume a value of Δρ of 0.8-10 3 kg / m 3 and T = 293 K (for simplicity), then h b is calculated for different values of the particle radius, resulting in the following list of values:

[0057] - R = 0.1 μm results in h b = 122 μm;

[0058] - R = 0.5 μm results in h b = 0.98 μm; and

[0059] - R = 1.4 μm results in h b = 45 nm.

[0060] Equation 3 shows that the height distribution of small particles is much larger than that of large particles. The large height distribution makes the average distance between the particle and the surface large, which is detrimental to the collision or encounter rate between the particle and the surface, thus hindering the effective association rate between the particle and the surface.

[0061] It should be noted that the mass density difference Δρ can be positive (i.e. the particle is heavier than the solution; the particle "sinks" to the biosensing surface) or negative (i.e. the particle is lighter than the solution; the particle "floats" to the biosensing surface).

[0062] Alternatively or in addition, the particle can be kept in close proximity to the surface by mechanical means, for example by a second surface which limits the height space in which the particle can reside, or which limits the accessible distance range between the particle and the first surface. It can serve as a means to keep the particle in the vicinity of the first surface and to prevent the particle from moving too far away from the first surface.

[0063] In another aspect, the second surface can be porous, such that the analyte and / or fluid can penetrate into the second surface, or penetrate through the second surface into and / or out of the region with the particle.

[0064] In another aspect, the first surface can be porous, such that the analyte and / or fluid can penetrate into the first surface, or penetrate through the first surface into and / or out of the region with the particles.

[0065] Large particles can provide a small height distribution and a small effective distance between the particle and the surface (see above). However, a small height distribution and a small effective distance can also hinder the reversibility of biomolecular interactions, resulting in a low dissociation rate. Large particles can create steric hindrance, thereby slowing down the association and dissociation processes (i.e. the transition of the biosensor device system of the present invention from its first state to its second state) and vice versa. Furthermore, even with the application of blocking and anti-fouling coatings on the particle and the surface, large particles can create non-specific interactions between the particle and the surface, including irreversible adhesion.

[0066] Biosensor device using particles with a diameter of 1 pm

[0067] Biosensor devices containing particles with a diameter of 1 pm or 2.8 pm were prepared. Two types of biosensor devices were prepared by using streptavidin-coated 1 pm particles (Dynabeads MyOne Cl), wherein 10 pM of the particle-binding agent biotin-oligonucleotide (SEQ ID NO: 1) was coupled to the particles via streptavidin. The remaining part of the particles was blocked using 100 pM of 1 kDa PEG-biotin and 1% BSA.

[0068] A surface (biosensor device A) was prepared by using 100 pg / mL of neutravidin (physically adsorbed), 500 nM of surface biotin-oligonucleotide (SEQ ID NO: 4) coupled to the surface via neutravidin, and using detection oligonucleotide molecules (SEQ ID NO: 3) coupled to the surface via biotin-oligonucleotide. The remaining part of the surface was blocked using 100 pM of 1 kDa PEG-biotin and 1% BSA.

[0069] Alternatively, another surface (biosensor device B) was prepared by using PLL-g-PEG and biotin-oligonucleotide coupled via click chemistry on a glass substrate.

[0070] The flow cell cartridge with measurement chamber was constructed using double-sided adhesive layers and a top plate with fluidic in- and outlets. Data was collected by exchanging the fluid in the flow cell, i.e. by continuously inserting solutions with different analyte concentrations. Fluids were inserted manually using a pipette. The flow rate in the experiments was typically in the range of about 1-300 microliters per minute.

[0071] As target, the analyte having SEQ ID NO: 2 was used.

[0072] Table 1. Synthetic DNA sequences used

[0073]

[0074]

[0075] Results DNA sandwich and competition assays

[0076] The data of biosensor device A indicate that the diffusion coefficient histogram and the measured state lifetimes depend on the analyte concentration provided to the flow cell. State lifetimes can be extracted because reversible transitions between associated and dissociated states are observed. State lifetimes show short and long term states, which can be attributed to different types (e.g. different valency) of interactions.

[0077] The example of biosensor device B shows measured diffusion coefficient histograms as a function of the analyte concentration provided to the flow cell; motility traces at a 10 pM concentration (free, single bond and multiple bond states are visible); and motility traces at a 50 pM concentration (single bond and multiple bond states are visible).

[0078] Insights provided by the biosensors of the invention

[0079] The data of the experiments indicate that:

[0080] - particle tracking can be performed with sufficient accuracy over sufficiently long time periods in case the associated and dissociated states of the particles of the biosensor device are clearly detected;

[0081] - the statistical analysis of the associated and non-associated state lifetime distributions shows a high sensitivity (picomolar range) of the dependence on the target concentration; and

[0082] - the distribution of the associated and non-associated state lifetimes exhibits multiple characteristic lifetimes (see: multi-exponential fit) and corresponding population fractions, which are related to transitions between different states (e.g. unbound state, state with single valency bond, state with multiple valency bond), all showing a target concentration dependence.

[0083] Due to the observation of different states (unbound, univalent bond, multivalent bond, etc.) different conversion rates and state lifetimes can be measured, which depend on the amount of target captured on the particle and surface and thus on the concentration of the target in solution. For example, when a particle is observed in univalent bond state or in case of a single molecule bond, additional bonds can be formed. This gives rise to lifetimes and conversion rates corresponding to the formation of the first bond and additional bonds, which depend on the concentration but differ in magnitude. This yields multiple parameters that can be extracted and used to improve the biosensing performance.

[0084] Important biosensing performance aspects of a biosensor are e.g. sensitivity, specificity, speed, reversibility, precision, accuracy, dynamic range, robustness, stability, multiplexing.

[0085] Furthermore, the measured lifetimes related to different states (e.g. single bond and multiple bond states) give information about the affinity of the molecules, e.g. association rate, dissociation rate and equilibrium binding constant, which can be used to characterize the properties of the molecules.

[0086] Furthermore, after filling the flow cell and starting the measurement, the observation in the measurement can be exchanged in the flow cell with minimal disturbance of the particles. Thus, the particle mobility assay without immobilization tethering can be used for continuous biomarker monitoring. Due to the reversible interaction, an increase and decrease of the analyte concentration can be followed.

[0087] Furthermore, changing the flow direction in the flow cell can help to compensate for the displacement and minimize the net distance the particles are displaced, which minimizes the loss of particles and enables measurements over long measurement sequences and long time spans.

[0088] With respect to the distance between the particle and the surface in the unbound state, a preferred distance is in the range of 5 nm to 10 pm. The lower limit (5 nm) is determined by the fact that molecular and reversible biomolecular interactions are typically operating on length scales of a few nanometers; there needs to be enough space between the particle and the surface to be able to obtain the unbound state. The upper limit (10 pm) is determined by the fact that there needs to be a sufficiently high collision rate between the particle and the surface to obtain an effective association rate, such that a sufficient conversion from the unbound state to the bound state can be observed.

[0089] Advantages of the assay without immobilization tethering (over the case with immobilization tethering):

[0090] - no tethering is required, thus less reagents and less processing steps are involved in the chemistry and sensor fabrication;

[0091] - due to the absence of immobilization tethering, the sensor is not dependent on tether stability or affected by tether degradation;

[0092] - there are less molecular components due to the absence of immobilization tethers, thus there are less physico-chemical constraints and a larger physico-chemical and (bio)chemical operating window, e.g. potentially a wider variety of buffers can be used, potentially a wider temperature range can be applied, etc.;

[0093] - sensors without immobilization tethers are easier to prepare, thus assay development, screening of reaction and preparation conditions, and technology development can be performed faster. Subsequently, the obtained technological knowledge can also be applied to develop sensors with immobilization tethers;

[0094] - less particles are needed to prepare a sensor, as the tethering process is typically of low efficiency;

[0095] - the particles have a rotational diffusion degree of freedom, such that interactions can occur on all faces of the particle (in case of immobilization tethers, the interaction area is limited to the area around the tether attachment point); this can improve kinetics and sensitivity; furthermore, as the interaction area per particle is larger (less sensitivity to physical and chemical heterogeneities on the particle), this can reduce variability and improve precision;

[0096] - the particles have a translational diffusion degree of freedom, thus association can be detected over a large surface area (in case of immobilization tethers, the interaction area is limited to the area around the tether attachment point); this can improve kinetics and sensitivity; and can reduce variability.

[0097] - the distance between the particles and the surface can be adjusted over a large range; such that also large analytes can be measured, e.g. nanoparticles, extracellular vesicles, exosomes, nanosomes, liposomes, virions, cells, cell fragments, supramolecular bodies, protein aggregates (immobilization tethers can sterically hinder the capture of large analytes between the particles and the surface);

[0098] - due to the large displacement of the particles, the non-associated state can be easily detected;

[0099] - the sensor can be prepared with dry particles (e.g. in a dissolvable matrix), such that the sensor can be activated by adding a fluid and used directly (this is more complex in case of immobilization tethers); and

[0100] - new particles can be added to the sensing chamber by providing a solution with particles; this can improve e.g. the cartridge measurement lifetime (see below).

[0101] Further aspects of the invention

[0102] The biosensor of the present invention is a system which can contain multiple components, e.g. for sampling an analyte from a system of interest (e.g. a biological system, an environmental system (e.g. river, pond, ocean, lake, source), a channel, a pipe, a tank, a well, an exhaust, a process, a reactor, a fermenter, a flow, an organism, a reservoir, a patient, an animal, an organoid), for pre-treating the sample (e.g. dilution, filtration, heating, enzymatic processing, separation), for guiding the sample to the sensing particle, for illuminating the particle, for collecting radiation from the particle, for imaging the particle, for determining spatial coordinate parameters of the particle at different points in time, for determining displacement or translation or rotation or motion parameters of the particle, for determining states in the time trajectory of the particle and binding and unbinding events, for processing histograms and parameter distributions, for converting processed parameters (e.g. amplitude, state, diffusion rate, diffusion constant, lifetime, rate, population in distribution, fractional occupancy, transition activity, event frequency, time delay) into analysis parameters (e.g. concentration, precision, accuracy, time profile), for converting analysis parameters into control actions (e.g. warning signals or closed loop control parameters), for controlling different components in the system (e.g. a computer with software) or for communicating with external components (e.g. a larger control system, a database, an internet system, an information system or a cloud system).

[0103] The biosensor of the present invention can contain a reader system (with e.g. optical components, components for data and signal processing, components for interface and data communication), a fluidic system (with e.g. methods for moving fluids or particles, pumps, methods for applying low or overpressure, methods for dilution, methods for mixing, vents, tubes, valves, filters, switches, flow sensors, pressure sensors, gas sensors, gas handling methods, degassing units, flow regulators, pressure regulators) or a cartridge or another container device (with e.g. openings, connectors, inlets, outlets, wells, channels, measurement surfaces, measurement chambers, alignment marks, identification marks, ID tags). The system can have containers for reagents (e.g. buffers, particles, pre-treatment reagents) or for collecting fluids (e.g. waste reservoirs). The sensor system can contain wet reagents or dry reagents (e.g. oven-dried or freeze-dried).

[0104] In another aspect, various fluid transport or particle transport or molecule transport or analyte transport structures can be used, such as in-plane transport, out-of-plane transport, cross-flow transport, convection, advection, diffusion. In another aspect of the sensor device, the sensor particles can be located in the vicinity of a first surface, wherein fluid transport or molecule transport or analyte transport occurs in different directions relative to the surface, such as in a direction along the surface and / or in a direction perpendicular to the surface; this includes transport through the surface. In another aspect, the particles can be located between a first surface and a second surface; transport of fluid, molecule or analyte can occur in different directions, such as along or through the different surfaces. The surfaces can be biofunctionalized to enable binding between the particles and the surface.

[0105] The cartridge and other components can be produced by patterning techniques (e.g., photolithography, contact printing, microcontact printing, non-contact printing, self-assembly), additive manufacturing (e.g., 3D printing), joining (e.g., gluing, welding, adhesive, tape), assembly, lamination, automated placement, molding, over-molding, drop casting, curing (e.g., optical, thermal). Other possible manufacturing techniques are, for example, biopatterning, biodeposition, bioconjugation, physisorption, drying, freeze-drying, irradiation, sterilization, packaging, sealing.

[0106] Modulating the sample or sample flow by chemical, biochemical or physical means can improve the analytical performance of the sensor, such as by stabilizing the pH, temperature, mass density of the solution (which, for example, is related to Δρ in equation 3), composition of the solution (e.g., absence of interfering molecules or cell aggregates), etc.

[0107] Particle detection and tracking can involve radiation, waves, electromagnetic principles, acoustics, scattering, fluorescence, absorbance, interference, plasmonic sensing, spectroscopic sensing, imaging, etc. The detection can allow for reliable tracking of individual particles.

[0108] In another aspect, in case optical detection methods are used, the cartridge and optical components can contain optically transparent materials, such as glass or polymers.

[0109] In another aspect, the height deviation of the method of tracking the coordinate parameters (e.g., depth of focus in case of some optical tracking methods) is preferably compatible with the height fluctuations of the particles (see, for example, equation 2), such that reliable tracking algorithms can be developed, and thus the probability of losing the particle trajectory due to height fluctuations is acceptable relative to other sources of error.

[0110] For example, the state of a particle can be determined accurately and / or precisely if the particle can be tracked for a time greater than the time required to determine whether the particle is in one state or another state. For example, the effective spatial coordinate parameter or the motion parameter can be determined accurately and / or precisely if the particle can be tracked for a time greater than the time required to determine the effective spatial coordinate parameter or the motion parameter. For example, the bound fraction, unbound fraction, and / or bound to unbound ratio can be determined accurately and / or precisely if a sufficiently high proportion of surface-interacting particles are tracked. For example, the characteristic state lifetime of a particle can be determined accurately and / or precisely if the particle can be tracked for a time greater than the characteristic state lifetime of the particle.

[0111] The biosensors of the present application can be prepared for immediate use, or rapid use, or plug-and-play, for example by incorporating particles stored in a fluid, or particles stored within a dissolvable matrix (which disperses and activates for sensing function in the measurement chamber upon wetting).

[0112] The biosensors of the present application can be used with a variety of binding agents, such as molecules, molecular constructs, and materials; for example, with oligonucleotides, proteins, peptides, polymers, aptamers, small molecules, sugars, molecularly imprinted polymers, and the like.

[0113] The association and dissociation state lifetimes in the system can be tuned by selection of, for example, binding agent, binding agent density, blocking method, buffer conditions, and the like.

[0114] If the average tracking time of individual particles is greater than the average association state lifetime and / or the average dissociation state lifetime of the particles, then multiple (un)binding events can be measured for each particle. This is advantageous for statistics and precision of derived parameters.

[0115] The biosensors of the present application can include components and methods for dissociating or removing particles from the sensor, for example by applying a fluidic mechanical resistance (such as a flow pulse) to the particles or fluid, an interfacial tension (such as a gas / liquid interface, a bubble), a field force (such as a magnetic field, an acoustic force, a light field), a thermal excitation, or other directed or random force. The biosensors of the present application 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 another force on the particles or fluid. Removal and / or addition can be useful to optimize the sensor, or to reset, regenerate, restart, or refresh the sensor.

[0116] It can be helpful to remove particles when they are no longer suitable for sensing (e.g. have become inactive, unresponsive, stationary or saturated). Adding or replacing particles can help to supply particles with good sensing properties or with different sensing properties, e.g. for sequentially measuring different analytes, or for sequentially sensing the same analyte at different points in time (particularly relevant if the relaxation time is long), or for sensing the same analyte with particles having different response properties (e.g. different sensitivity or specificity).

[0117] The biosensor of the present application can have mixed sensing particles, e.g. particles with immobilized tethers and particles without immobilized tethers, or particles with different optical properties and / or sensing properties (e.g. for multiplexing).

[0118] The biosensor of the present application can be used to measure affinity parameters of molecules and / or particle-surface combinations and distributions of affinity parameters.

[0119] The biosensor of the present application can be used for continuous monitoring, intermittent testing and end-point measurements, e.g. for use when needed or in a laboratory environment.

[0120] The biosensor of the present application can be used for e.g. industrial process monitoring, life science applications, medical applications, fermentation, bioreactors, patient care, clinical trials, pharmaceutical applications, environmental monitoring, field environmental testing, home environmental monitoring, extraterrestrial testing, air quality monitoring, vapor testing, respiratory fluid testing, water quality monitoring, chemical monitoring, closed loop control, real-time monitoring, early warning systems, etc. BRIEF DESCRIPTION OF DRAWINGS

[0121] Figure 1 A schematic of a biosensor device of the present application is shown, in which both the particle 1 and the surface 2 are functionalized by a first moiety 3 and a second moiety 4. The analyte of interest 5 is also visualized. Figure 1 The biosensor device as shown is in its second dissociated state: the functionalized particle 1 is not associated with the functionalized surface 2. Figure 1

[0122] Figure 2 shows a schematic of a biosensor device of the present application, in which sensing of the analyte of interest 5 is measured by using a sandwich assay, in which the analyte of interest 5 is sandwiched between the first moiety 3 of the particle 1 and the second moiety 4 of the surface 2, bringing the particle 1 and the surface 2 into association (i.e. the first state of the present application). Figure 2A A schematic of the biosensor device is shown, in which the analyte 5 is not sensed by the biosensor. Figure 2B

[0123] ​​Figure 3 shows a schematic of a biosensor device of the application in which sensing of an analyte of interest 5 is measured by using a competition assay in which a first portion 3 of the particle 1 binds to a second portion 4 of the surface 2 Figure 3A ) or the analyte of interest 5 binds to a portion 4 of the surface 2 Figure 3B .

[0124] Figure 4 An example of a flow cell cartridge suitable for use as a biosensor device of the application is shown. The flow cell cartridge comprises an inlet 10, a flow channel 11 and an outlet 12.

[0125] Figure 5 Results of measuring particles of 1 μιη diameter in an oligonucleotide-based sandwich assay at a ssDNA target concentration of 125 pM are shown. Figure 5 The left-hand graph shows the 2D motion pattern reconstructed from the xy trajectory data. Figure 5 The middle graph shows the diffusion coefficient as a function of time, showing both the free Brownian motion and the restricted Brownian motion induced by target-induced sandwich formation between the particle and the substrate. The threshold is set at D = 0.1 μιη 2 / s 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). Figure 5 The right-hand graph shows a histogram of the calculated diffusion coefficient values, showing a Gaussian-like distribution for the unbound state, and a peak below the threshold for the bound state. For this configuration with 125 pM target (incubation concentration of 500 nM substrate-side binder and 10 μΜ particle-side binder), about 15% of the total particles show single-molecule binding. At a target concentration of 250 pM, this increases to about 30%. Note also that the measurement starts 2 minutes after addition of the target (analyte to be sensed by the biosensor).

[0126] Figure 6 A plurality of diffusion coefficient histograms for an oligonucleotide-based sandwich assay with 1 μιη diameter particles is shown. A Gaussian-like curve is observed in the buffer (PBS) with a mean D of about 0.25 μιη 2 / s. Upon addition of the ssDNA target molecules, the particles can bind to the substrate in a sandwich fashion, and thus the diffusion coefficient decreases. This is reflected in the histogram by the appearance of a peak at D < 0.15 μιη 2 / s. The prominence of the peak increases with increasing target concentration.

[0127] Figure 7 A plurality of diffusion coefficient histograms for an oligonucleotide-based sandwich assay with 1 μιη diameter particles is shown. A Gaussian-like curve is observed in the buffer (PBS) with a mean D of about 0.25 μιη Figure 6Survival curves of the bound state lifetimes are presented for the same experimental data. These plots show the lifetimes (x-axis, linear scale) and their survival fraction (y-axis, log scale) at different target concentrations. The cumulative distribution function (CDF) of all bound state lifetimes is determined and the survival fraction is defined as 1 - CDF (points in the plots). The characteristic bound state lifetimes are extracted based on a bi-exponential fit of the state lifetime survival curves (solid lines in the plots). The first exponent represents the short bound state lifetimes, which are attributed to the single molecule binding mode (τ sm ). This characteristic lifetime remains relatively constant upon addition of target, as the lifetime only depends on the affinity binder properties. The second exponent represents the longer bound state lifetimes, which are attributed to multivalent binding (τ mv ). The fraction of multivalent binding observed in this experiment as well as the characteristic lifetimes increase with increasing target concentration.

[0128] Figure 8 Unbound state lifetime survival curves are presented for the same experimental data as Figure 6 These plots show the lifetimes (x-axis, linear scale) and their survival fraction (y-axis, log scale) at different target concentrations. As for the bound state lifetimes, the characteristic unbound state lifetimes are extracted based on a bi-exponential fit of the state lifetime survival curves (solid lines in the plots). The first exponent (τ1) represents the short unbound state lifetimes (<10 s), which are attributed to non-specific interactions as well as measurement and analysis artefacts; these are independent of the target concentration. The second exponent (τ2) is attributed to the unbound state lifetimes associated with molecular binding, which are inversely proportional to the target concentration. As the target concentration increases, particles bind to the substrate more frequently and the time between binding events shortens. This is reflected in the decrease of the characteristic unbound state lifetimes.

[0129] Figure 9 A schematic of the ssDNA sandwich assay experiment with PLL-PEG functionalization is shown. Particles are functionalized with a particle side binder having 11 bp complementary to the ssDNA target. Using second generation click chemistry, a DBCO-labelled substrate side binder is coupled via the integrated azido group to the physisorbed PLL-g-PEG polymer. The reversible 9 bp hybridization between the substrate side binder and the ssDNA target results in transient binding of the particle. In the presence of the target, the particle can bind to the surface due to the target-induced sandwich bond and can be converted from the unbound state (left) to the single or double bound state (right).

[0130] Figure 10Results are shown for a DNA sandwich assay performed with single stranded DNA targets of concentrations 1 pM, 10 pM and 100 pM added sequentially to the sensor. The position of the particles is tracked at a frame rate of 60 Hz over a duration of 10 minutes. A histogram of the diffusion coefficients of the set of particles is plotted for each concentration, showing the unbound and bound populations as a function of target concentration.

[0131] Figure 11 Examples of single particle trajectories and the corresponding evolution of the diffusion coefficient are shown. Single stranded DNA targets of concentration 10 pM are added to perform the DNA sandwich assay explained in Figure 9 B. The position of the particles is tracked over a duration of 10 minutes and the particle trajectories can be reconstructed (inset). The diffusion coefficient of each particle is computed as a function of time and binding / unbinding events are detected for all particles in the field of view.

[0132] Figure 12 Examples of single particle trajectories and the corresponding evolution of the diffusion coefficient are shown. Single stranded DNA targets of concentration 50 pM are added to the system shown in Figure 9 and a five minute measurement is performed. In these examples, the particles mainly switch between a single bound state and a double bound state. Time traces with two bound states are shown, corresponding to the time span marked by different grey colors in the inset. The particles show a pancake-like motion pattern in the single bound state and a rod-like or dot-like motion pattern in the double bound state.

[0133] Figure 13 The basic principle of a monitoring biosensor based on the measurement of the free long-range diffusion motion of biologically functionalized particles with reversible molecular binding to a substrate is shown. Figure 13 A shows a microparticle functionalized with a particle-side binding agent. The particle diffuses in the vicinity of a substrate functionalized with a substrate-side binding agent. The binding agent has a specific affinity for a target molecule. A target-induced sandwich complex is reversibly formed and causes the particle to switch between an unbound state and a bound state. The particle exhibits free Brownian motion in the unbound state and restricted Brownian motion in the bound state. Figure 13 The right panel of A shows a microscope image of about 500 particles in a field of view of about 500 pm x 500 pm. The inset shows reconstructed in-plane trajectories of a subset of particles (n ~ 25) tracked for 300 s. Figure 13 B shows experimental data for a sandwich system with oligonucleotide binding agents and targets. Figure 13 The left column of B shows trajectories of single particles in the absence (top) and presence (bottom) of target molecules in solution. The black dots in the bottom panel indicate the bound state caused by a target-induced sandwich bond. Figure 13The right column of B shows the diffusion parameter D calculated as a function of time based on the in-plane displacement derived from the particle trajectories. In the absence of analyte (top), the particles typically exhibit free Brownian motion. In the absence of analyte (bottom), the particles show a transition from the unbound state (gray) to the bound state (black). The state transition is represented by a binary step function (line above). Figure 13 C shows the distribution of D for about 500 particles measured, showing the unbound (gray) and bound (black) populations depending on the target concentration.

[0134] Figure 14 Trajectories of the mobility and state lifetime are shown for 1 μιη and 2.8 μιη diameter particles. Figure 14 A shows the diffusion coefficient. Figure 14 D shows the values measured over a 5 minute time period, showing the unbound (gray) and bound (black) states. Figure 14 B shows the distribution of D derived from single particle trajectories in A, illustrating the difference between 1 μιη and 2.8 μιη particles. Figure 14 C shows the D distribution for hundreds of particles. Figure 14 D shows the distribution of unbound state lifetimes plotted as survival curves for 1 μιη and 2.8 μιη particles with similar biofunctionalization and target concentrations. Under comparable conditions, the larger particles exhibit shorter unbound state lifetimes than the smaller particles. The inset shows the same data on a lin-lin scale. Figure 14 E shows the survival plot as in D, here for the bound state lifetimes. The curve segments are attributed to monovalent bonds of short lifetime and multivalent bonds of long lifetime.

[0135] Figure 15 A DNA-based sandwich assay using 2.8 μιη particles is shown. Figure 15 A shows the survival curves characteristic of the unbound state lifetime, showing the dependence on target concentration. As the DNA sandwich target concentration is increased, the survival curves become steeper (black arrows), reflecting the shorter times between binding events. Figure 15 B shows the characteristic unbound state lifetime (circles) as a function of target concentration in the range 30-500 pM, and the dashed scale as about [T] -1.6±0.1The characteristic unbound state lifetime (triangles) is independent of target concentration with an average value of 13 ± 2 s (dashed line). The lifetimes of 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 are the standard deviation of the lifetime fit and are typically smaller than the symbol size. The inset shows the neutravidin substrate functionalized with ssDNA binding agent combined with 2.8 pm particles functionalized with different ssDNA binding agents. The ssDNA target strands are also depicted. Figure 15 C shows the dose-response curve in terms of activity fitted with a Hill equation with an EC50 of 65 ± 4 pM. The inset shows the response in terms of fraction bound with an EC50 of 240 ± 40 pM. The dashed line represents the 95% confidence interval of the Hill equation fit. Figure 15 D shows the continuous monitoring of individual target concentrations and reversibility of the sensor (fitted with an exponential decay function, solid line). Figure 15 The lower panel of D shows the sandwich target concentrations applied in a stepwise manner over time followed by a wash with buffer. Figure 15 The upper panel of D shows that the measured conversion activity increases with increasing target concentration over time and reversibility is demonstrated within 90 min. The sensor functionality is maintained after the wash step with buffer.

[0136] Figure 16 The response of the sensor to target concentration is shown for a ssDNA competition assay in PBS and filtered undiluted plasma using 1 pm particles. The 1 pm particles are functionalized with a particle-side binding agent via biotin-streptavidin interaction and DNA hybridization. A DBCO-labeled substrate-side binding agent is coupled to the PLL-g-PEG polymer via an integrated azido group using second generation click chemistry. The reversible 9 bp hybridization between the substrate-side binding agent (which also serves as ssDNA analog) and the particle binding agent leads to transient binding of the particle. In the presence of the 11 -nt target, the binding region on the particle-side binding agent is blocked, resulting in a decrease in the fraction bound and conversion events. Figure 16 A shows the sensor response curves, i.e. the fraction bound and conversion activity as a function of target concentration, fitted with a Hill equation. The black and grey curves represent two consecutive measured dose-response curves at decreasing concentration series, which demonstrate the reversibility of the sensor and its suitability for monitoring applications. Figure 16 B shows the characteristic unbound state lifetime dependent on target concentration in the range of 10 to 2000 nM. Figure 16 C shows the measured conversion activity for ssDNA targets in 50 kDa spin-filtered bovine plasma. Figure 16 D shows the characteristic unbound and bound state lifetimes measured in filtered bovine plasma.

[0137] Figure 17 A reversible sensor for detecting the sepsis biomarker procalcitonin (PCT) using an antibody sandwich immunoassay is shown. Data from two sensor devices are shown. The glass substrate was functionalized with 100 nM capture antibody (c-Ab) by physical adsorption and subsequently blocked with 1% BSA in PBS (blocking buffer). Streptavidin-coated 2.8 pm Dynabeads were functionalized with 100 nM biotinylated detection antibody (d-Ab), blocked with 100 pM biotinylated PEG (1 kDa) and blocked with blocking buffer. The d-Ab functionalized microparticles were diluted to 66 pg / mL in PBS with 0.1% BSA (assay buffer) and injected to the c-Ab functionalized sensor surface. The analyte PCT was added to the assay buffer and 30 pL of the solution was injected into the sensor flow-through chamber. Each injection was performed under flow reversal (i.e. alternating supply at the inlet or outlet) to minimize loss of particles in the effective field of view of the sensor. Washing was performed with assay buffer injection, identical to the PCT measurement, at least 3 times to reach the baseline fraction of bound particles (open symbols). Particle motion was tracked under brightfield illumination at 60 Hz for 10 minutes. The data clearly show the monitoring function of the sensor, i.e. the response of the sensor to PCT concentration and the reversibility of the sensor.

[0138] Further information

[0139] In other embodiments of the devices or methods of the application, the biosensor can not be in direct contact with the system of interest, or can be in direct contact with the system of interest. Alternatively, the biosensor can be embedded or integrated or implanted into the system of interest. The biosensor can be placed at a distance from the system of interest. However, the biosensor can be located in the vicinity of the system of interest, on the system, wirelessly integrated, etc. The sample can be placed in a container and then transported to the biosensing system (sometimes referred to as online or offline operation), the sample can be collected and automatically transported to the biosensing system (sometimes referred to as online operation), or the biosensing system can be fully integrated with the system of interest (sometimes referred to as online or bypass operation).

[0140] In other embodiments of the application, the devices or methods can be connected or integrated into an industrial system or process, a fermenter, a bioreactor, an on-body device, a catheter, an in-vivo device, a wearable device, or a concealable device.

[0141] In a biosensing system with monitoring functionality, time-dependent samples can be acquired, measurement data can be recorded, and a time profile of the analyte concentration over time can be established. Furthermore, the biosensor can be configured to receive a series of samples (from the same or different sources), wherein the series of samples is measured consecutively on the biosensor and time-dependent data related to the different samples that have been supplied to the biosensor is generated.

[0142] In other embodiments of the application, the device or method can be combined with a method or device module for sample pre-treatment or analyte pre-treatment (e.g. reagent addition, dilution, filtration, extraction, enrichment, purification, separation, amplification, change of buffer conditions, stabilization, (de-)aggregation or removal, modification or addition of chemical groups or biochemical domains or residues or moieties).

[0143] In other embodiments of the application, the device or method can be combined with a method or device module for optimizing or controlling operation (e.g. temperature, humidity, pressure, light conditions, vibration conditions, sound conditions, sterility, hygiene, access protection, cleaning, part replacement, ease of maintenance, calibration, etc.). SEQUENCE LISTING <110> Eindhoven University of Technology <120> Biosensor utilizing particle motion <130> PA230346C <150> NL2026320 <151> 2020-08-21 <160> 4 <170> BiSSAP 1.3.6 <210> 1 <211> 11 <212> DNA <213> Artificial Sequence <220> <223> Particle binding agent <400> 1 agcatggcac t 11 <210> 2 <211> 22 <212> DNA <213> Artificial Sequence <220> <223> Analyte <400> 2 tcgtaccgtg agtaataatg cg 22 <210> 3 <211> 31 <212> DNA <213> Artificial Sequence <220> <223> Detection <400> 3 cattattaca agctaagctc ttgcactgac g 31 <210> 4 <211> 25 <212> DNA <213> Artificial Sequence <220> <223> Surface binding agent <400> 4 cgattccaga acgtgactgc ttttt 25

Claims

1. A biosensor device for continuously, repeatedly, or intermittently sensing an analyte over a time period using particle motion, the biosensor device having a surface and particles, wherein the particles and / or the surface are functionalized, and wherein: - The biosensor device has a first state in which the particle is associated with the surface and a second state in which the particle is not associated with the surface; and The transition between the first and second states depends on the presence, absence, and / or concentration of the analyte. The motion characteristics of the particles are thus variable depending on the presence, absence, and / or concentration of the analyte, thereby allowing the analyte to be sensed by measuring the spatial coordinate parameters of the particles relative to the surface. The properties of the particles and the surface are selected such that, in the second state, the particles are near the surface, enabling the biosensor to measure changes in the spatial coordinate parameters of the particles relative to the surface. The particles are not attached to the surface.

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

3. The biosensor device according to claim 1, wherein the first state in which the particle associates with the surface includes a first association state and a second association state, wherein: - The first association state includes monomolecular bonds between the particle and the surface; and - The second association state includes two or more monomolecular bonds between the particle and the surface.

4. The biosensor device according to claim 1, wherein the biosensor device comprises at least 10 particles.

5. The biosensor device according to claim 4, wherein the biosensor device comprises at least 100 particles.

6. The biosensor device of claim 1, wherein the biosensor device comprises a 415 × 415 µm... 2 The density of a few particles to thousands of particles in the region.

7. The biosensor device of claim 1, wherein the biosensor device comprises a diffraction-limited optical system, and the biosensor device comprises particles that are separated from the nearest neighbor particle by at least the diffraction-limited optical system.

8. The biosensor device according to claim 1, wherein the biosensor device performs binding assays, competitive assays, displacement assays, sandwich assays, enzymatic assays, assays utilizing target and / or signal amplification, multi-step assays, or assays utilizing molecular cascades.

9. The biosensor device according to claim 1, wherein: - The particle is functionalized by a first portion, wherein the first portion is combined with the particle; or The surface is functionalized by a second portion, wherein the second portion is integrated with the surface. The portion thereof has a binding affinity for the analyte.

10. The biosensor device according to claim 1, wherein: - The particle is functionalized by a first portion, wherein the first portion is incorporated into the particle; and The surface is functionalized by a second portion, wherein the second portion is integrated with the surface. Depending on the presence, absence, or concentration of the analyte, the components have binding affinity to each other.

11. The biosensor device according to claim 9 or 10, wherein: - The dissociation rate constants of the analyte and the first fraction differ by at least a factor of 3 relative to the dissociation rate constants of the analyte and the second fraction; or - The first portion and the second portion differ by at least a factor of 3 relative to the analyte and the first portion and / or relative to the analyte and the second portion in dissociation rate constant.

12. The biosensor device of claim 11, wherein the dissociation rate constants of the analyte and the first portion differ by at least a factor of 5 relative to the dissociation rate constants of the analyte and the second portion.

13. The biosensor device of claim 11, wherein the first portion and the second portion have dissociation rate constants that differ by at least a factor of 5 relative to the analyte and the first portion and / or relative to the analyte and the second portion.

14. The biosensor device according to claim 9 or 10, wherein the biosensor device has a [10] […]. 0 Up to 10 8 Parts / µm 2 The density of a portion within the range.

15. The biosensor device of claim 14, wherein the portion associated with the particle or the surface has a [value] at 10 [units]. 1 Up to 10 7 Parts / µm 2 10 2 Up to 10 6 Parts / µm 2 Or 10 3 Up to 10 5 Parts / µm 2 Density within the range.

16. The biosensor device according to claim 9 or 10, wherein the first portion or the second portion is a protein, carbohydrate, molecularly imprinted polymer, nucleic acid, multivalent binder, or a combination thereof.

17. The biosensor device of claim 16, wherein the first portion or the second portion is an antibody, antibody fragment, recombinant protein, peptide, sugar, DNA molecule, PNA molecule, or aptamer.

18. The biosensor device according to claim 16, wherein the first part or the second part is a nanobody.

19. The biosensor device according to claim 9 or 10, wherein the first portion or the second portion is a binding molecule for electrolytes, metabolites, carbohydrates, hormones, drugs, proteins, oligonucleotides, nanoparticles, exosomes, nanobodies, liposomes, viral particles, cells, or cell debris.

20. The biosensor device of claim 19, wherein the first portion or the second portion is a binding molecule for glucose, lipids, peptides, drug metabolites, DNA, RNA, extracellular vesicles, or protein aggregates.

21. Use of the biosensor device according to any one of claims 1-20 in a method of performing multiplexing.

22. The use according to claim 21, wherein the biosensor device is used to perform a method of analyte multiplexing, spatial multiplexing, spectral multiplexing, or probe function multiplexing.

23. Use of the biosensor device according to any one of claims 1-20 as a sensor, wherein the sensor is on or in or as part of a system for sensing or detection, the system comprising an endoscope, tube, needle, fiber, catheter, patch, disposable probe, flow cell, or disposable cartridge.

24. Use of the biosensor device according to any one of claims 1-20 for in vivo biosensing, out-of-vivo biosensing or in vitro biosensing for non-diagnostic purposes.

25. The use according to claim 24, wherein the biosensor device is used for in vitro diagnostic testing, point-of-care testing, environmental testing, food testing, process monitoring, process control, forensic medicine, biology, biomedical and pharmaceutical research, or for monitoring assays using living cells, tissues or organs.

26. A method for sensing an analyte using particle motion, the method comprising: a) Contacting a matrix containing the analyte with the biosensor device according to any one of claims 1-20; and b) Detect the kinematic properties of the particles, which vary depending on the presence, absence, and / or concentration of the analyte. The motion characteristics mentioned therein include the spatial coordinate parameters of the particle relative to the surface.

27. The method of claim 26, wherein the particles: -Arranged to transition from the first state to the second state with an average effective dissociation time; and -Arranged to transition from the second state to the first state with an average effective association time, and Step b) of detecting the motion characteristics of the particles is performed over a period of time longer than the average effective dissociation time and / or the average effective association time.

28. The method according to claim 26 or 27, wherein in step b), the flow direction of the matrix containing the analyte changes continuously or intermittently.

29. The method of claim 28, wherein the change in flow undergoes a change in random flow direction or a change in reverse flow direction.

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