Air staged injection of fluids in flow cells for SPR analysis

Abstract

According to various aspects, the present invention provides a method of delivering a plurality of sample solutions to a sensor surface (102) for analysis. It may additionally or alternatively provide systems and methods for enabling an improved study of analyte behavior. A sensor (102) may be used, for example, to determine kinetic binding properties of an analyte, such as a protein, to a surface binding ligand. In one aspect, a method includes: a) introducing (902) a first sample solution (502) into a first channel (506), the first channel (506) configured to deliver the sample solution to a sensor surface (102); b) introducing (904) a second sample solution (504) into the first channel (506); c) flowing (906) the first sample solution and the second sample solution through the first channel (506) and over the sensor surface (102); and d) detecting (912) at the sensor surface (102) the presence or absence of binding of the analyte from at least one of the sample solutions (502, 504) wherein no running buffer solution passes over the sensor surface (102) throughout steps a)-d).

Description

Technical Field

[0001] The present disclosure relates to analysis of sample solutions at a sensor surface, and more particularly, to systems and methods for delivering multiple sample solutions to the sensor surface and / or for enabling improved studies of analyte behavior. Background Art

[0002] Analytical sensor systems capable of real-time monitoring of interactions between molecules (e.g., biomolecules) are gaining increasing interest. Such systems typically enable determination of one or more of binding, kinetics, affinity, specificity, and concentration of a molecule ('analyte') contained in a sample solution. Optical biosensors are particularly useful for this purpose and are often referred to as interaction analysis sensors or biospecific interaction analysis sensors. Representative such biosensor systems are sold by Cytiva An instrument that uses surface plasmon resonance (SPR) to detect interactions between molecules at a sensing surface without any need for labels. As the corresponding sample passes over the sensor surface, the progress of binding can be measured and provides a direct reflection of the rate at which the interaction between the molecules occurs.

[0003] From the system (e.g. The typical output of a binding system is a graph or curve describing the progression of a molecular interaction over time, including a portion of the association phase and a portion of the dissociation phase. Such a binding curve, usually displayed on a computer screen, is often referred to as a 'sensogram'. The system (and similar sensor systems), without the use of labels and generally without involving purification of the material, can determine in real time not only the presence and concentration of a specific analyte in a sample, but also additional interaction parameters, including the kinetic rate constants for binding (association) and dissociation in the molecular interaction, and the affinity of the interaction being evaluated. The association rate constant (ka) and dissociation rate constant (kd) can be obtained by fitting the resulting kinetic data for a number of different sample analyte concentrations to a mathematical description of the interaction model in the form of a differential equation. The affinity (expressed as the affinity constant K A or dissociation constant K D ) can be calculated from the association and dissociation rate constants. Affinity values ​​may also be measured by equilibrium binding analysis, which involves determining the level of binding at equilibrium or steady state for a range of analyte concentrations, which is believed to be reached at or near the end of the association phase of the binding interaction.

[0004] Traditionally, such analysis involves analyzing the interaction between a molecule bound at the sensor surface (usually referred to as a 'ligand') and a molecule of interest in an injected sample solution (usually referred to as an 'analyte'). In this traditional approach, a running buffer is passed over the sensor surface between injections of different sample solutions. This running buffer is typically composed to mimic physiological conditions to stabilize the ligand and analyte. Typical buffer solutions include ingredients such as Hepes, TRIS or phosphate ions to maintain a pH close to 7.4, 150 mM sodium chloride, 3 mM EDTA, and 0.05% detergent P20.

[0005] However, the inventors have recognized that in some cases, it would be useful to analyze not only the interaction of an analyte with an immobilized ligand, but also or alternatively to analyze the interaction between two or more analytes or sample compositions injected in succession. For example, it would be useful to inject a first sample solution containing a first analyte, followed by a second sample solution containing a second analyte, and determine how and whether the first and second analytes interact. However, existing systems and methods are not effective in facilitating such 'polyinjection' analysis. In particular, the inventors have recognized that in existing systems, the use of a running buffer between samples makes such analysis difficult because the first analyte is washed away, dissociated or disturbed before the second analyte can reach the sensor surface.

[0006] The inventors have also recognized that current analytical methods do not always achieve accurate and efficient analysis of sample behavior. In particular, current methods are poorly optimized for detecting binding signals from weakly bound analytes when forming complexes with another analyte (or ligand) that produces a significantly stronger binding response. Current methods are also poorly optimized for determining whether a binding response signal represents a given reaction or binding event of interest. More generally, existing sample assay methods are limited in their application and effectiveness.

[0007] It would be advantageous to provide systems and methods that address one or more of the above-mentioned problems, either alone or in combination. In particular, it would be advantageous to provide improved sample assay methods and systems. Summary of the invention

[0008] This Summary introduces concepts that are described in greater detail in the Detailed Description. It should not be used to identify essential features of the claimed subject matter, nor should it be used to limit the scope of the claimed subject matter.

[0009] According to one aspect of the present disclosure, there is provided a method of delivering a plurality of sample solutions to a sensor surface for analysis, comprising: a) introducing a first sample solution into a first channel, the first channel being configured to deliver the sample solution to the sensor surface; b) introducing a second sample solution into the first channel; c) flowing the first sample solution and the second sample solution (502, 504) through the first channel and over the sensor surface; and d) detecting the presence or absence of binding of an analyte from at least one of the sample solutions (502, 504) at the sensor surface. Throughout steps a)-d), no running buffer solution is passed over the sensor surface.

[0010] This method provides a robust and reliable mechanism for performing 'multi-injection' analysis, in other words, analysis involves two or more sample solutions introduced sequentially without running buffer. "Running buffer" in this context includes a continuous buffer flow provided by a running buffer reservoir, which can be introduced into the system and flows over the sensor surface to wash away the analyte. Therefore, such running buffer is to be contrasted with the sample solution introduced into the system. Different from the continuous running buffer, in this context, the sample solution is a discrete, highly controlled volume of liquid, which is provided to achieve the behavior of the analyte at the sensor surface. The sample solution is usually provided from a sample bottle or a microplate. Preventing the running buffer from entering the system during the analysis (e.g., until all sample solutions have been sequentially injected and analyzed) avoids any interference of such sample solutions or sensor surfaces by the running buffer. It will be appreciated that the disclosed method is not limited to only two sample solutions. On the contrary, any number of sequential samples can be provided.

[0011] Preferably, the second sample solution is separated from the first sample solution in the first channel by a gas segment. More generally, if more than two sample solutions are used, each solution can be separated from any previous sample in the first channel by a corresponding gas segment. The use of a gas segment between consecutive sample solutions ensures that there is no (or minimal) mixing between consecutive solutions in the first channel. This means that the samples will only interact once they reach (or approach) the sensor, meaning that this interaction occurs at the sensor and can be analyzed. Note that the term 'interaction' is synonymous with the term 'reaction' in this article.

[0012] Preferably, the gas segment is extracted from the first channel via the second channel before the gas segment reaches the sensor surface, so that the gas segment does not contact the sensor surface.

[0013] This is advantageous because in some cases, if the gas segment is allowed to reach the sensor surface, it may interfere with the measurement and generate unwanted signals or noise. The gas segment may also interfere with or even damage the sensor surface (or the ligand or analyte immobilized / captured there). Extracting the gas segment before it reaches the sensor surface prevents this, while still allowing the gas segment to prevent sample mixing throughout most of the sample's journey through the first channel towards the sensor. Due to the disclosed method, a reliable mechanism for performing multi-injection analysis is provided. In particular, the behavior of the first and second sample solutions (and typically the analytes contained therein) at the sensor surface can be reliably analyzed.

[0014] Preferably, introducing the first and second sample solutions into the first channel comprises aspirating the first and second sample solutions from respective first and second sample solution reservoirs and injecting the sample solutions into the first channel. Such a mechanism enables accurate and reliable introduction of a specific volume of sample solution into the system. Typically, the sample solution reservoir comprises a vial with a stopper that is pierced by a needle during aspiration and injection. However, other sample solution reservoirs may also be used.

[0015] Preferably, the above steps a)-d) are performed using a first pump, which is configured to introduce the sample solution into the first channel and flow the sample through the first channel and over the sensor surface. The first pump can be contrasted with different running buffer pumps, which can include a separate pump configured to introduce a continuous running buffer into the system. Using different pumps to introduce sample solution and running buffer enables accurate multi-injection analysis. In particular, the sample analysis pump can be operated during the analysis, while the running buffer pump remains inactive. This prevents the introduction of continuous running buffer during the analysis, which has the above advantages. Once the analysis is completed, the sample analysis pump can be deactivated, and the running buffer pump can be activated to clean the system and the sensor surface, and the reading is reset to a baseline value. In particular, before step a) and / or after step d), the running buffer obtained from the running buffer reservoir is preferably passed over the sensor surface by the running buffer pump.

[0016] Preferably, the gas segment is extracted at most 40 seconds before the second sample solution reaches the sensor surface. This time threshold ensures that there is a sufficiently short time window during which the sample solutions can mix before they reach the sensor surface. This is beneficial because the short time window ensures that the mixing (and therefore the interaction) between the sample solutions before reaching the sensor surface is negligible. This ensures that the reaction occurs at the sensor surface and can therefore be analyzed. The short mixing window before reaching the sensor surface is particularly important for the study of fast reactions, such as the various examples described in the implementation section below.

[0017] As described above, the disclosed method can be performed for more than two sample solutions. Preferably, the method is performed for three or more sample solutions, wherein each sample solution is separated from any previous sample solution in the first channel by a corresponding gas segment. This allows interactions between a large number of sample solutions to be analyzed, which in turn enables more complex applications of the disclosed technology, as described in the following implementations and examples.

[0018] The sensor surface may have a ligand immobilized thereon, and step d) as described above may comprise detecting the presence or absence of binding of an analyte from at least one sample solution to the ligand on the sensor surface. This enables more efficient performance of analysis of how successive samples interact with the ligand, particularly in the presence of another analyte.

[0019] Step d) may additionally or alternatively include identifying whether an analyte in one of the sample solutions is bound to an analyte in another of the sample solutions, which has previously been bound to the sensor surface. For example, a first analyte from a first sample may be bound to the sensor surface, and step d) may then include identifying whether a second analyte from a second sample solution is bound to an analyte from the first sample solution. Such an analysis enables a more efficient implementation of studies of how successive samples interact.

[0020] Preferably, the first and second sample solutions are introduced into the first channel in a first order, and the method further comprises repeating method steps with the first and second sample solutions introduced into the first channel in a second order different from the first order. For example, sample A may be introduced in the manner described herein, followed by sample B. The interaction between A and B at the sensor surface may then be analyzed. The method may then be repeated, but this time sample B is introduced first, followed by sample A. This enables analysis of how the samples may interact when arriving at the ligand or sensor surface in a different order. This may inform analysis of preferred binding sites for the analyte.

[0021] Although some implementations of the disclosed method involve the injection of multiple samples, each sample containing a corresponding analyte, in some cases, it may be beneficial to inject one or more samples that do not contain an analyte. For example, a first sample solution may have a first pH value and include a first analyte, and a second sample solution may have a second pH value and does not include an analyte. In an example of this implementation, the first sample may include a buffer solution of a specific form having a specific pH value (e.g., 7.4). The first sample solution includes a first analyte of interest, which is configured to bind to a ligand (or other analyte) at the sensor surface. Then, the second sample may include a buffer solution of the same form having a different pH value (e.g., 6.0) but not containing an analyte. When the second sample solution flows over the sensor surface, it is then possible to determine how changes in pH affect the analyte already bound to the sensor surface. This enables a more complex analysis of how the analyte behavior is affected by the pH environment.

[0022] The first and second sample solutions may have first and second respective concentrations, and the method may further comprise modifying the concentration of at least one of the first and second sample solutions and repeating the method steps using the modified solution(s). This enables analysis of how analyte interactions are affected by analyte concentration.

[0023] Each sample solution may include a different corresponding analyte, or may include the same analyte.

[0024] As described above, at least one sample solution may include a buffer. A sample solution of a buffer is contrasted with a continuous running buffer flow. In particular, a sample solution of a buffer includes a specific volume of buffer provided via a sample injection pump or similar sample injection mechanism in the same manner as any other sample solution, typically from a sample bottle. In the context of analyzing the behavior of an analyte at the sensor surface, a buffer sample is injected. This is contrasted with a running buffer flow, which is provided from a buffer reservoir by a buffer reservoir pump and whose sole purpose is to 'flush' and wet the system before or after performing an assay.

[0025] Compared to an unspecified volume of running buffer, an accurately measured buffer sample (also referred to as a 'buffer pulse' or 'blank sample') provided as a sample solution in the context of the present method can be used to more efficiently perform various forms of analysis, as described in the following implementations and examples. For example, the use of a buffer sample can tell how the absence of a specific analyte affects the binding response, can be used to detect response signals that would otherwise be drowned by other signals, and can be used to assess the kinetics of an analyte. In an illustrative example, an assay can be performed using two consecutive sample solutions that include a first and a second analyte, respectively. A second assay can then be performed after the assay, wherein the first sample is a blank (does not contain analyte) and the second sample contains the same analyte as the second sample in the first assay. The binding observed in the first and second assays can then be compared. If binding of the second sample occurs in both assays, then it has been determined that the second analyte binds to the ligand. On the other hand, if binding of the second sample occurs only in the first assay and not in the second assay, then it has been determined that the second analyte binds only in the presence of the first analyte, i.e., not directly to the ligand. In that case, it can be said that the binding of the second analyte depends on the first analyte. This and many other example analyses are made possible by using a blank or buffer sample within the assay.

[0026] The at least one sample solution may include at least one of: an antibody; an antigen; an enzyme; an agonist; an antagonist; a wash solution; or a sensor surface regeneration solution.

[0027] The first sample solution may contact the sensor surface during a first time period, and the second sample solution may contact the sensor surface during a second time period. The first and second time periods may be referred to as the 'contact time' of the first and second samples. The delay between the end of the first time period and the beginning of the second time period (i.e., the gap between the two contact times) is preferably 40 seconds or less. This time threshold ensures that the disclosed method is suitable for analyzing interactions involving analytes that dissociate or degrade rapidly. For example, the first injected analyte in the first sample may bind to the sensor surface, but then dissociate quickly. Ensuring that the second sample arrives within 40 seconds or less ensures that for a wide range of implementations, the second sample will arrive in time for the interaction of interest to occur at the sensor before the first analyte dissociates. More preferably, the delay between the first and second samples is 30 seconds or less, 20 seconds or less, 10 seconds or less, or 1 second or less. These successively shorter time periods ensure that even very rapidly dissociating analytes can be analyzed. This time range is possible through the methods and systems disclosed herein because there is no 'downtime' caused by the injection of intermediate running buffer. For example, the exact time between the first and second samples arriving at the sensor can be determined by the length of the flow channel through which the samples flow between gas segment extraction and the sensor. The disclosed methods and available time ranges between samples mean that an assay environment can be developed around and modified to suit a specific analyte of interest.

[0028] More generally, the methods disclosed herein are particularly useful for analyzing rapidly interacting analytes. This is because mixing in the first channel is prevented before the sample approaches the sensor surface. Therefore, transient interactions occur at the sensor surface and can be detected and analyzed at the sensor surface. In addition, in the case of ligands that bind to the sensor surface, there is no intermediate running buffer step between sample injections, meaning that the next sample can be provided before the analyte of the first sample has partially or completely dissociated from the sensor surface, which is important for analyzing various types of interactions.

[0029] The first sample solution may include a membrane protein, and the second sample solution may include a lipid configured to at least partially cover the membrane protein. Such membrane proteins may be particularly susceptible to interference from the running buffer flow. Therefore, the method disclosed herein is particularly well served to analyze such membrane proteins and their interactions with lipids, which can avoid the presence of a running buffer throughout the analysis.

[0030] The volume of the at least one sample solution introduced into the first channel can be determined based on a target duration during which the at least one sample solution is present at the sensor surface. For example, the required volume of the sample can be determined based on a known or predetermined flow rate of the sample and a predetermined target duration during which the sample will be present at the sensor surface.

[0031] The method may also include identifying complexes accumulated on the sensor surface, the complexes comprising analytes from at least two of the sample solutions. The methods disclosed herein are particularly suitable for analysis of complexes requiring rapid delivery of analytes (e.g., due to the rapid dissociation times of the analytes involved), which can avoid running buffer delays in providing the next sample to the sensor surface.

[0032] Similarly, the method may further include identifying whether the corresponding analytes in the first and second sample solutions compete for binding sites (at the ligand or at the analyte previously bound to the sensor surface). In that case, it is important that the second analyte arrives when the first analyte is still substantially present at the surface (otherwise it would be impossible to accurately determine whether there is competition). This is facilitated by the currently disclosed method, which enables the second sample to arrive soon after the first sample because there is no waiting during the injection of the running buffer during it. In addition, for example, the exact time at which the sample arrives at the sensor surface can be calibrated by the length of the first flow channel.

[0033] The method may further comprise identifying whether an analyte included in at least one of the sample solutions binds to the same or a different epitope as an analyte included in another of the sample solutions. When using the disclosed method, such binding properties can be particularly easily analyzed because interference by a running buffer flow is avoided.

[0034] Step d) of the above method may be based on evanescent wave sensing or surface plasmon resonance (SPR).

[0035] The gas section may include air, nitrogen, or another inert gas that does not affect the sample solution. Using air is generally the most straightforward and causes the least complications.

[0036] The sensor surface can include silver or gold. While using a silver sensor surface can provide the best sensor performance, silver has a tendency to degrade over time. Gold is more resilient and does not deteriorate over time in aqueous solutions. It is also simple to attach organic molecules to gold.

[0037] The first and second channels may form a generally T-shaped junction which provides good performance.Any other junction shape may be used as long as there are at least three flow directions: from the sample reservoir; to the sensor; and the outlet channel of the gas section.

[0038] According to another aspect of the present disclosure, there is provided a sample analysis system, comprising a first channel and a sensor surface. The sample analysis system is configured to perform the following steps: a) introducing a first sample solution into the first channel, the first channel being configured to deliver the sample solution to the sensor surface; b) introducing a second sample solution into the first channel; c) allowing the first sample solution and the second sample solution to flow through the first channel and over the sensor surface; and d) detecting the presence or absence of binding of an analyte from at least one of the sample solutions at the sensor surface, wherein throughout steps a)-d), no running buffer solution is passed over the sensor surface.

[0039] More generally, a sample analysis system configured to perform any of the methods disclosed herein is disclosed. Note that the terms 'biosensor system' and 'sample analysis system' are used interchangeably herein. The terms "sample" and "sample solution" are also used interchangeably herein and refer to a specific volume of fluid, typically containing an analyte of interest, suitable for introduction into the system during sample analysis at a sensor surface.

[0040] According to another aspect of the present disclosure, there is provided a method for delivering multiple sample solutions to a sensor surface for analysis, comprising: a) introducing a first sample solution into a first channel, the first channel being configured to deliver the sample solution to the sensor surface; b) introducing a second sample solution into the first channel, wherein the second sample solution is separated from the first sample solution by a gas segment in the first channel; c) allowing the first sample solution, the second sample solution and the gas segment to flow toward the sensor surface through the first channel; d) extracting the gas segment from the first channel via a second channel before the gas segment reaches the sensor surface, so that the gas segment does not contact the sensor surface; e) allowing the first sample solution and the second sample solution to flow over the sensor surface; and f) detecting the presence or absence of a binding of an analyte from at least one of the sample solutions at the sensor surface. Such a method enables continuous and accurate analysis of multiple sample solutions. As described above, mixing of sample solutions is prevented. Preferably, no running buffer is provided to the system through steps a)-f), which has the above-mentioned associated benefits.

[0041] According to another aspect of the present disclosure, there is provided a method for assaying multiple groups of sample solutions, comprising providing a first group of sample solutions, wherein the first group of sample solutions comprises at least three sample solutions. The method further comprises obtaining a first binding signal by performing an assay using the first group of sample solutions, during which each sample solution in the first group of sample solutions flows sequentially over a sensor surface.

[0042] The term "sequentially" in this context means one after another, optionally with intermediate gas segments and / or running buffer or other washing solutions provided between samples, as described more fully below.

[0043] It will be appreciated that when each sample solution in the first set of sample solutions flows over the sensor surface, it will generate a corresponding response signal indicating the presence (or absence) of the binding of the analyte in that sample solution at the sensor surface. For example, a solution comprising an analyte that strongly binds to a ligand or other analyte present at the sensor surface will generate a large response signal. A solution comprising a weakly bound analyte will generate a small response signal, while a sample that does not contain an analyte (e.g., a buffer sample) or a sample that contains an unbound analyte will not generate a binding response signal. Therefore, the "first binding signal" of the first set of sample solutions as defined herein includes a combination of these continuous individual response signals generated by the corresponding sample solutions in the first set of sample solutions during the assay. Therefore, the first binding signal can be considered to be the total or composite binding signal of the first set of sample solutions.

[0044] The method also includes providing a second set of sample solutions, wherein the second set of sample solutions includes a subset of the first set of sample solutions and a buffer sample solution. In the present disclosure, the term "subset" means "the same solution but at least one less". Therefore, if the first set of sample solutions includes solutions A, B, and C, then the second set of sample solutions may include solutions A and B but not C, or A and C but not B, etc. Replace the omitted sample solution and provide a sample of the buffer solution in the second set of sample solutions.

[0045] As defined herein, a "buffer sample" (also referred to as a 'buffer pulse' or 'blank sample') is a sample solution that is provided during an assay in the same manner as any other sample solution from a sample reservoir, but contains only buffer and no analyte. Thus, when the buffer sample reaches the sensor surface, it does not generate a binding response signal. As described below, the use of a buffer sample during an assay can yield important insights into the binding characteristics of other analytes in the assay. Note that a buffer sample is to be contrasted with a running buffer. As defined herein, a running buffer is provided to a sample solution from a running buffer reservoir via a different mechanism (e.g., via the following Figure 4The sensor is provided with a discrete running buffer pump (shown in FIG. 1 ) and its sole purpose is to wash out the analyte at the end of the assay and to keep the instrument wet when there is no sample flow. This is in contrast to a buffer sample, which is provided like any other sample from a sample reservoir and which has a discrete, highly controlled volume and is injected for the purpose of analyzing the behavior of the analyte at the sensor surface.

[0046] The method also includes obtaining a second binding signal by performing an assay using the second set of sample solutions, during which each sample solution in the second set of sample solutions is sequentially flowed over the sensor surface. As previously described, the "second binding signal" herein consists of a combination of consecutive individual response signals generated by corresponding sample solutions in the second set of sample solutions during the assay. Thus, the second binding signal can be considered to be a total or composite binding signal of the second set of sample solutions.

[0047] The method also includes generating a third binding signal by subtracting the second binding signal from the first binding signal. Therefore, the third binding signal can be considered as a difference signal indicating the difference between the first and second binding signals. The third binding signal can be displayed for analysis by the user, or used for computational analysis by the system. As will be described more fully below, the third (or difference) binding signal can reveal previously hidden analyte behavior, and reveal interactions and relationships that are not obvious from the first or second binding signal alone. Therefore, the disclosed method provides an improved method for sample assay, which allows more effective and diverse research on analyte behavior.

[0048] Providing the first and / or second set of sample solutions may include introducing the respective sample solutions into a channel configured to deliver the sample solutions to the sensor surface. Preferably, each sample solution introduced into the channel is separated from any previous sample solution in the channel by a respective gas segment. This prevents the samples from mixing before they reach the sensor surface, thereby allowing more efficient analysis, as discussed more fully below. Preferably, before each gas segment reaches the sensor surface, the method includes extracting the respective gas segment from the channel via another channel so that each respective gas segment does not contact the sensor surface. This ensures that the gas segment does not damage the sensor surface, as described more fully below, while still enabling the gas segment to prevent mixing of the sample throughout most of the sample's journey through the first channel toward the sensor. Due to the disclosed method, a reliable mechanism for performing sample assays is provided. In particular, the behavior of the sample solution (or more precisely, the analyte contained therein) at the sensor surface can be reliably analyzed.

[0049] Preferably, introducing the first and / or second group of sample solutions comprises aspirating the corresponding sample solutions from the corresponding sample solution reservoirs and injecting the sample solutions into the channels. Such a mechanism enables accurate and reliable introduction of a specific volume of sample solution into the system. Typically, the sample solution reservoir comprises a vial with a stopper that is pierced by a needle during aspiration and injection. However, other sample solution reservoirs may also be used.

[0050] Obtaining the first and / or second binding signal may include detecting the presence or absence of binding involving an analyte from the corresponding sample solution at the sensor surface. For example, the sensor surface may have a ligand immobilized thereon. In that case, obtaining the first and / or second binding signal may include detecting the presence or absence of binding of an analyte from at least one sample solution to the ligand on the sensor surface. This enables more efficient performance of analysis of how successive samples interact with the ligand, particularly in the presence of another analyte.

[0051] Alternatively or additionally, obtaining the first and / or second binding signal may comprise detecting the presence or absence of binding between analytes from two or more sample solutions at the sensor surface. This enables more efficiently performing analysis of how consecutive samples interact with each other.

[0052] In an advantageous implementation, the first set of sample solutions includes a first sample solution and a second sample solution, wherein, when the second sample solution reaches the sensor surface, the first sample solution generates a dissociation signal equal to or greater than the association signal generated by the second sample solution, and wherein the second set of sample solutions does not include the second sample solution. In cases such as these, when the response decrease (dissociation) from the first sample solution is significant compared to the response increase (association) from the second sample solution, the response signal from the second sample solution will become obscured. In particular, the composite signal formed by the combination of the first sample dissociation and the second sample association will be flat (if the signals are equal) or negative (if the first sample dissociation is greater than the second sample association). In such a case, when using conventional analysis, it is virtually impossible to accurately analyze the (association) binding response of the second sample solution because it is masked to such an extent by the (dissociation) binding response of the first sample solution. As a result, it may be impossible to accurately determine the presence or magnitude of the binding of the second sample. The present method overcomes this problem because the binding response signal of the first sample solution is effectively removed by subtracting the second binding signal. Thus, the calculated third (ie, differential) binding signal reveals a response of the second sample solution that would otherwise have been obscured. Thus, more efficient sample analysis is possible.

[0053] In another advantageous implementation, the first group of sample solutions includes a first sample solution and a second sample solution, wherein the analyte in the second sample solution can bind to the analyte in the first sample solution and the ligand on the sensor surface, and wherein the second group of sample solutions does not include the first sample solution. In conventional analysis, it is difficult to determine whether the binding response signal associated with the second sample solution is the result of the second sample solution (or, in particular, the analyte therein) binding to the analyte in the first sample solution or binding to the ligand. This is usually solved by introducing a so-called "blocking" molecule, which blocks the binding to the ligand so that only the binding between the sample solutions occurs and is detected. However, as described more fully below, using blocking is complicated and time-consuming. The present method realizes revealing the binding between the first and second sample solutions without using blocking molecules, because the binding between the second sample solution and the ligand is effectively removed by subtraction. Therefore, the third (i.e., difference) binding signal only contains signals related to the interaction of interest between the first and second sample solutions. Therefore, more effective sample analysis becomes possible again.

[0054] It will be appreciated that the terms "first" and "second" herein are merely labels used to denote sample solutions in the first set of sample solutions. Thus, these terms do not imply any absolute (or even relative) order of injection. For example, in some cases, the "first" sample solution may be the second of three (or more) sample solutions injected from the first set of sample solutions.

[0055] In a further advantageous implementation, the first set of sample solutions includes a first antibody, an antigen, and a second antibody. In that case, the second set of sample solutions may not include the antigen. This enables the binding between the second antibody and the ligand to be detected (in the second binding signal) and removed by subtraction. Therefore, the third (i.e., differential) binding signal reveals the binding between the second antibody and the antigen, wherein the "noise" from any binding of the second antibody to the ligand is removed.

[0056] In an advantageous implementation, the method further comprises determining, based on the third binding signal, whether the binding of the analyte in the second sample solution in the first group of sample solutions depends on the presence of the analyte from the first sample solution in the first group of sample solutions. For example, this can be revealed by whether there is a response signal left after subtracting the second binding signal. The method allows for more effective study of correlations in binding, such as studying whether the second sample requires the presence of the first sample to be bound. It will be appreciated again that the terms "first" and "second" are merely labels used here to represent sample solutions in the first group of sample solutions, and do not imply any absolute or relative order of injection. For example, in an assay, one or more sample solutions may be injected before the "first" sample solution.

[0057] In another advantageous implementation, the method further comprises determining whether the analyte in the first sample solution in the first group of sample solutions is bound to the same epitope as the analyte in the second sample solution in the first group of sample solutions based on the third binding signal. For example, this can be revealed again by whether there is a response signal left after subtracting the second binding signal. The method allows for a more effective study of competition for epitopes between analytes, such as studying whether the first sample binds to the same epitope as the second sample. This can be used to identify epitope competition between the first and second antibodies and between an antibody and another molecule (e.g., a receptor). As described above, it will be appreciated again that the terms "first" and "second" are merely labels for representing sample solutions in the first group of sample solutions and do not imply any absolute or relative order of injection. For example, in an assay, one or more sample solutions may be injected before the "first" sample solution.

[0058] Each sample solution may include a different corresponding analyte, or may include the same analyte.

[0059] The at least one sample solution may include at least one of: an antibody; an antigen; an enzyme; an agonist; an antagonist; a wash solution; or a sensor surface regeneration solution.

[0060] The volume of the at least one sample solution introduced into the first channel can be determined based on a target duration during which the at least one sample solution is present at the sensor surface. For example, the required volume of the sample can be determined based on a known or predetermined flow rate of the sample and a predetermined target duration during which the sample will be present at the sensor surface.

[0061] Performing an assay using the first and / or second set of sample solutions may be based on evanescent wave sensing or surface plasmon resonance (SPR).

[0062] It will be appreciated that the methods disclosed herein are not limited to two assays. Instead, any suitable number of assays may be performed to generate a corresponding number of binding signals. These binding signals may then be subtracted from one another to generate a desired number of difference signals. Examples involving more than two assays will be described in more detail below.

[0063] According to another aspect of the present disclosure, there is provided a sample analysis system, comprising: a sensor having a surface on which a sample solution can flow; and at least one channel, the at least one channel being configured to deliver the sample solution to the sensor surface. The sample analysis system is configured to: provide a first set of sample solutions to the at least one channel, wherein the first set of sample solutions includes at least three sample solutions; perform an assay in which each sample solution in the first set of sample solutions flows sequentially over the sensor surface to obtain a first binding signal; provide a second set of sample solutions to the at least one channel, wherein the second set of sample solutions includes a subset of the first set of sample solutions and a buffer sample solution; perform an assay in which each sample solution in the second set of sample solutions flows sequentially over the sensor surface to obtain a second binding signal; and generate a third binding signal by subtracting the second binding signal from the first binding signal.

[0064] More generally, a sample analysis system configured to perform any of the methods disclosed herein is disclosed. Note that the terms 'biosensor system' and 'sample analysis system' are used interchangeably herein. The terms "sample" and "sample solution" are also used interchangeably herein and refer to a specific volume of fluid, typically containing an analyte of interest, suitable for introduction into the system during sample analysis at a sensor surface. References to binding of a sample or binding of a sample solution should be interpreted as references to binding of an analyte contained in the sample (solution).

[0065] According to another aspect of the present disclosure, there is provided a computer configured to cause a sample analysis system to perform any method disclosed herein. In other words, any of the disclosed methods can be implemented by a computer.

[0066] According to another aspect of the present disclosure, there is provided a computer-readable storage medium comprising instructions that, when executed by a computer, cause the computer to cause a sample analysis system to perform any of the methods disclosed herein. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] Illustrative implementations of the present disclosure will now be described, by way of example only, with reference to the accompanying drawings. In the drawings:

[0068] Figure 1 A schematic diagram of a SPR-based biosensor system is shown;

[0069] Figure 2 A representative sensorgram showing the detector response versus time for interactions between molecules occurring at the sensor surface is shown;

[0070] Figure 3shows a schematic diagram of the BIACORE T200 from Cytiva, which is an example of a biosensor system that can be used to implement the disclosed methods;

[0071] Figure 4 shows a schematic diagram of a sample delivery system, such as may be found in a biosensor system for implementing the disclosed methods;

[0072] Figure 5 A sequence of four sample injections (AD) analyzed under the prior method is shown, whereby a continuous injection of running buffer occurs between the injections of each sample;

[0073] Figure 6 shows a sequence of four sample injections (AD) analyzed using the new and improved method of the present disclosure, as a result of which, in a process referred to herein as 'multi-injection', samples can be injected sequentially without intermediate running buffer;

[0074] Figure 7a shows first and second sample solutions flowing through a channel, wherein mixing occurs at the sample interface;

[0075] Figure 7b shows first and second sample solutions flowing through a channel, wherein mixing is prevented by a gas segment;

[0076] Figure 8a-8c An example mechanism for preventing a gas segment in a flow channel from contacting a sensor surface is shown;

[0077] Figure 9a-9c Shown are the binding signals obtained by running an assay with three analytes injected in three corresponding sequences;

[0078] Fig.10a and Fig.10b Another binding signal obtained by running an assay with three analytes is shown, while Fig.10b Shows Fig.10a A close-up of a portion of the graph;

[0079] Figure 11a-Figure 11c The first and second binding signals obtained by the corresponding assays are shown, and Fig.11c shows a difference curve obtained by subtracting the second binding signal from the first binding signal;

[0080] Figure 12a-Figure 12c The third and fourth binding signals obtained by the corresponding assays are shown, and Fig.12c shows another difference curve obtained by subtracting the fourth binding signal from the third binding signal;

[0081] Figure 13a-Figure 13c The fifth and sixth binding signals obtained by the corresponding assays are shown, and Fig.13c shows another difference curve obtained by subtracting the sixth binding signal from the fifth binding signal;

[0082] Figure 14a-14d The seventh, eighth and ninth binding signals obtained by the corresponding assays are shown, and Fig.14b Shows Fig.14a Close-up of a part of a graph. Fig.14c shows the difference curve obtained by subtracting the eighth binding signal from the seventh binding signal, and Fig.14d shows a difference curve obtained by subtracting the ninth binding signal from the seventh binding signal;

[0083] Fig.15a Schematic representation of a complex that can be established on a sensor surface, comprising a ligand, two antibodies, and an antigen;

[0084] Fig.15b and Fig.15c Shown by Fig.15a The tenth and eleventh binding signals obtained from the corresponding assays associated with the complexes Fig.15d shows another difference curve obtained by subtracting the eleventh binding signal from the tenth binding signal;

[0085] Fig.16a shows various difference signals obtained by the cyclic subtraction method of the present invention;

[0086] Fig.16b A summary table showing epitope competition between three antibodies, whose behavior has been determined using the method of the invention;

[0087] Fig.16c shows that the same Fig.16a The results of the same protocol;

[0088] Fig.17 The steps of a method for assaying multiple sets of sample solutions are shown;

[0089] Fig.18 The steps of a method for delivering a plurality of sample solutions to a sensor surface for analysis are shown; and

[0090] Fig.19 Components of an example computer device that may be used to implement the methods described herein are shown.

[0091] Like reference numerals denote like features throughout the specification and drawings.The drawings are not necessarily drawn to scale. DETAILED DESCRIPTION

[0092] refer to Figure 1-Figure 4 , which describes the basic principles of a biosensor (also called a sample analysis system) and its method of operation. Figure 5 The conventional mechanism for analyzing a sample solution in a biosensor is described. Then, an improved method for performing such an analysis is also described. Finally, reference is made to Fig.19 , describes components of an example computer device that can be used to implement the methods described herein.

[0093] The systems and methods disclosed herein generally relate to delivering a variety of sample solutions to a sensor surface for analysis. By preventing the flow of running buffer between sample injections, samples can be sequentially delivered to the sensor surface without interference or delay. This mechanism of sequentially providing samples to the sensor surface without intermediate running buffer is referred to as a 'multi-injection' procedure or assay in this article. Various features and methods for optimizing such multi-injection assays are also disclosed herein. In particular, due to the introduction of a gas segment to keep the sample solutions separated, mixing of sample solutions in a flow channel leading to the sensor surface can be substantially avoided. By removing the gas segment before the gas segment arrives at the sensor surface, damage or interference at the sensor surface can be avoided. The disclosed systems and methods achieve more effective interaction analysis and provide specific utility for various analyte binding analyses, as described more fully below.

[0094] Chemical sensors or biosensors are usually based on label-free technology, detecting changes in sensor surface properties (such as mass, refractive index or thickness of a fixed layer). There are also other forms of sensors that rely on some kind of label. Typical sensor detection technologies include, but are not limited to, mass detection methods such as optical, thermo-optical and piezoelectric or acoustic wave methods (including, for example, surface acoustic wave (SAW) and quartz crystal microbalance (QCM) methods), and electrochemical methods (such as potentiometric, conductivity, current and capacitance / impedance methods). Regarding optical detection methods, representative methods include those that detect mass surface concentrations, such as reflectance optical methods, including external and internal reflection methods (which are angle-, wavelength-, polarization- or phase-resolved), such as evanescent wave ellipsometry and evanescent wave spectroscopy (EWS or internal reflection spectroscopy), both of which can include evanescent field enhancement via surface plasmon resonance (SPR), Brewster angle refractometry, biolayer interferometry (BLI), critical angle refractometry, frustrated total reflection (FTR), scattered total internal reflection (STIR) (which can include scattering-enhanced labels), optical waveguide sensors; external reflection imaging, evanescent wave-based imaging (e.g., critical angle-resolved imaging), Brewster angle-resolved imaging, SPR angle-resolved imaging, etc. Furthermore, mention may be made (either "by itself" or in combination with reflectance methods) of photometric and imaging / microscopy methods based on, for example, surface enhanced Raman spectroscopy (SERS), surface enhanced resonance Raman spectroscopy (SERRS), evanescent wave fluorescence (TIRF) and phosphorescence, as well as waveguide interferometry, waveguide leakage mode spectroscopy, reflection interferometry spectroscopy (RIfS), transmission interferometry, holographic spectroscopy and atomic force microscopy (AFR).

[0095] Commercially available biosensors include the above-mentioned ones manufactured and sold by Cytiva of Uppsala, Sweden. System instrumentation, which is based on surface plasmon resonance (SPR) and allows real-time monitoring of surface binding interactions between analytes (molecules) of interest. Other biosensors may also be used.

[0096] Typical analytes that can be used in the context of the present disclosure include, but are not limited to, proteins and glycoproteins (e.g., antibodies or fragments thereof, affibodies or aptamers), enzymes, receptors, antigens, haptens, peptides, chemical molecules (e.g., drug candidates or fragments thereof, specific or non-specific binders, chelators or aggregators), lipids, and carbohydrates.

[0097] The term "antibody" describes a natural or partially or completely synthetically produced immunoglobulin. Antibodies can be monoclonal or polyclonal and can be prepared by techniques well known in the art, such as immunizing a host and collecting serum (polyclonal), or by preparing a continuous hybrid cell line and collecting secreted proteins (monoclonal), or by cloning and expressing a nucleotide sequence or a mutagenized version thereof to encode at least the amino acid sequence required for the specific binding of a natural antibody. The term "antibody" also encompasses any polypeptide or protein including an antibody antigen binding site. Antibody fragments including an antibody antigen binding site include, but are not limited to, molecules such as Fab, Fab', Fab'-SH, scFv, Fv, dAb, Fd; and diabodies. Methods for generating sensing surfaces for use in biosensor systems are well known in the art. For example, multiple examples of such methods are described in US5492840 and US5242828, and the contents of US5492840 and US5242828 are incorporated herein by reference.

[0098] Although the following detailed description and examples describe the systems and methods generally in SPR spectroscopy and more specifically in The disclosed systems and methods are shown in the context of the present invention, but it is to be understood that the disclosed systems and methods are not limited to such detection methods. Instead, any affinity-based detection method can be employed in which interactions between analytes and / or between analytes and ligands at a sensing surface can be detected, as long as a change at the sensing surface can be measured that quantitatively indicates binding or interaction.

[0099] The SPR phenomenon is well known and can be said to occur when light is reflected under certain conditions at an interface between two media with different refractive indices, and this interface is covered by a metal film (usually silver or gold). In the instrument, the medium is the sample solution and the glass of the sensor chip, which is in contact with the sample through a microfluidic flow system. The metal film is a thin layer of gold on the surface of the chip. SPR causes a decrease in the intensity of reflected light at a specific reflection angle. This angle of minimum reflected light intensity varies with the refractive index of the surface on the side opposite to the reflected light, and In the system, the side is the sample side.

[0100] exist Figure 1 A schematic diagram of SPR analysis is shown in The SPR analysis is performed in the system. The sensor chip 101 has a gold film 102 supporting a capture molecule (ligand) 103 (e.g., an antibody). A first sample solution 105 flows over the sensor surface, exposing the sensor surface (and the ligand 103 thereon) to an analyte 104, such as an antigen, included in the first sample solution 105. Figure 1 In the context of and more generally in the present disclosure, the phrase "flowing over" means that the sample solution flows over the sensor surface and, in so doing, contacts the sensor surface, thereby enabling any analyte in the sample solution to interact with suitable capture molecules on the sensor surface. Thus, the term "over" should not be interpreted as requiring any absolute direction. For example, Figure 1 As shown in FIG. 1 , the flow channel 105 can actually be below the sensor 101. The sensor (and flow path) can also be arranged in a manner similar to Figure 1 The directions shown in FIG. 1 and FIG. 2 may be oriented 90 degrees to each other, or in any other orientation.

[0101] Monochromatic p-polarized light 106 from a light source 107 (e.g., an LED) is coupled by a prism 108 to a glass / metal interface 109 where the light is totally reflected. The intensity of the reflected light beam 110 is detected by an optical detection unit 111 (e.g., a photodetector array). When molecules in the sample solution (e.g., analyte 104) bind to capture molecules (e.g., ligand 103) on the surface of the sensor chip, the concentration and therefore the refractive index at the surface changes, and an SPR response is detected. During the interaction process, plotting the response versus time will provide a quantitative measure of the progress of the interaction. Such plots or kinetic or binding curves (binding isotherms) are often referred to as response signals or sensorgrams, sometimes also referred to in the art as 'affinity traces' or 'affinity diagrams'. In In the system, the SPR response is expressed in resonance units (RU). One RU represents a 0.0001° change in the angle of minimum reflected light intensity, which for most proteins and other biomolecules corresponds to approximately 1 pg / mm on the sensor surface. 2 When a sample containing analyte contacts the sensor surface, the capture molecules bound to the sensor surface interact with the analyte in a step called "association". This step is indicated on the sensorgram by an increase in RU when the sample initially contacts the sensor surface. In contrast, "dissociation" typically occurs when the sample solution is replaced by, for example, a running buffer flow, at which time the analyte is removed from the surface. This step is indicated on the sensorgram by a decrease in RU over time as the analyte dissociates from the surface-bound ligand.

[0102] Representative sensorgrams (binding curves) of reversible interactions at the sensor chip surface are shown in Figure 2. The binding curves produced by the biosensor systems based on the other detection principles described above will have a similar appearance. In this example, the sensing surface has a fixed capture molecule (e.g., ligand), such as an antibody, thereon. When the solution flows over the sensor surface, this interacts with the binding partner (analyte) in the sample solution. The vertical axis (y-axis) indicates the response (here in resonance units RU), and the horizontal axis (x-axis) indicates the time (here in seconds). Initially, the running buffer is passed continuously over the sensing surface, giving a baseline response K in the sensor diagram. The sample solution containing the analyte of interest is then injected. During the sample injection, an increase in the signal is observed due to the binding of the analyte to the ligand at the sensor surface. This portion L of the binding curve is generally referred to as the "association phase". Ultimately, a steady-state condition is reached at or near the end of the association phase, when the resonance signal reaches a plateau at M (however, this state may not always be reached). It should be noted that the term "steady state" is used synonymously with the term "equilibrium" herein (in other contexts, the term "equilibrium" can be retained to describe an ideal interaction model, because in practice, even if the system is not in equilibrium, binding can remain unchanged over time). At the end of the sample injection, the sample is replaced again by the running buffer of the continuous flow, and the reduction of the signal reflects the dissociation or release of the analyte from the sensor surface. This part N of the binding curve is generally referred to as the "dissociation phase". The analysis usually ends with a regeneration step, wherein a solution that can remove the bound analyte from the surface while (ideally) maintaining the ligand activity is injected over the sensor surface. This is indicated in part O of the sensor diagram. However, in the case where the dissociation has been completed or is expected to be completed before the next analysis, regeneration can be avoided, which has the advantages of enhancing ligand preservation and reducing the number of operations. The injection of the continuous running buffer restores the baseline K, and the surface is now ready for a new analysis.

[0103] From the profiles of the association and dissociation phases L and N, respectively, information about the binding and dissociation kinetics is obtained, and the height of the resonance signal at M represents the affinity (the response resulting from the interaction associated with the change in mass concentration on the surface). US2012 / 0244637A1 discloses methods for determining, for example, surface binding rates, kinetic rate constants ka and kd, affinity constants (association constant K A and the dissociation constant K D) and other parameters. Software for analyzing kinetic and affinity data is commercially available. Thus, for example, evaluation of kinetic and affinity data generated by a BIACORE instrument is typically performed using a dedicated BIACORE Insight Evaluation Software (provided by Cytiva of Uppsala, Sweden), which uses numerical integration to calculate differential rate equations and nonlinear regression to fit kinetic and affinity parameters by finding the values ​​of the variables that give the closest fit, thereby reducing the residual sum of squares to a minimum. Further discussion of the methods can be found in U.S. Pat. No. 5,313,264. A detailed discussion of the technical aspects of the instrument and the SPR phenomenon is provided in, for example, U.S. Patents Nos. 5,242,828 and 5,436,161 for more detailed information on substrate coatings for biosensor sensing surfaces. In addition, a detailed discussion of the SPR phenomenon can be found in U.S. Patent Nos. 5,492,840. A detailed discussion of technical aspects of the biosensor chip used in conjunction with the instrument.The above-mentioned publications, as well as any other publications, patent applications, patents, or other references mentioned in this disclosure, are incorporated herein by reference in their entirety.

[0104] Figure 3 A schematic diagram of an example sample analysis system (also referred to as a biosensor system) that can be used to implement the disclosed methods is shown. In the example shown, the analysis system 300 is manufactured by Cytiva T200 instrument. It will be appreciated that this is a non-limiting example of a biosensor system and that the components described below can be generalized to other forms of biosensor systems. More generally, the disclosed methods can be combined and applied to a variety of other biosensor systems operating under similar principles and are not limited to Implementation in the system.

[0105] The analysis system 300 includes a sample chamber 302, which is Figure 3 The sample chamber 302 can be opened and a sample solution (typically stored in one or more sample reservoirs, such as Figure 4302) can be inserted into chamber 302. Once sealed, observation window 306 allows observation of sample solution within chamber 302 from the outside. During analysis, a sample delivery system (also referred to as a fluid handling system) delivers sample solution from a sample reservoir stored within sample chamber 302 to the sensor surface, as described more fully below. At its simplest, the sample delivery system includes a network of at least one pump and flow channels for routing samples and running buffer through analysis system 300 and to the sensor. The sensor can be inserted and removed via sensor chip port 304 before / after analysis. Continuous running buffer can be provided from buffer reservoir 308 via a buffer pump (not shown) housed in buffer pump chamber 310. Waste material can be collected in waste reservoir 312.

[0106] Figure 4 An example sample delivery system 400 is shown, which may be used, for example, in a biosensor system (eg, Figure 3 The sample delivery system 400 includes a fluid box 402, which is configured to receive a sample solution from a sample solution reservoir (e.g., a sample bottle or a microplate) stored in a sample array 406. In the example shown, a needle 408 is used to extract a sample solution from a corresponding reservoir (e.g., a vial), and the needle 408 can aspirate the sample and then inject the sample into the fluid box. Other mechanisms for sample delivery will be apparent. The fluid box 402 is also configured to receive a running buffer from a running buffer reservoir 308. A running buffer pump 404 is used to control the running buffer flow. Once a sample solution or running buffer is received at the fluid box 402, it can be provided to the sensor via one or more flow channels (not shown), as described in more detail below. The sample solution is preferably delivered to the fluid box and / or the sensor surface under the action of a sample delivery pump (not shown) different from the running buffer pump 404. This allows the sample delivery and running buffer delivery to be controlled separately. Alternatively, a single pump may switch between drawing running buffer from reservoir 308 and drawing sample solution from sample array 406, as needed. Waste solution may be drained from the sensor surface and flow channels via fluid cartridge 402 to waste reservoir 312.

[0107] Now go to Figure 5 and Figure 6 When using a sample analysis system, it is often desirable to analyze the behavior of multiple analytes in succession. For example, a first sample A containing analyte A' is injected. Analyte A' binds to the ligand on the sensor surface and then dissociates when a running buffer flow is introduced. Subsequently, the process is repeated for samples B, C, and D containing the corresponding analytes B', C', and D'. Figure 5The response curves associated with this approach are shown schematically (and by simplified outline) in FIG. This approach allows comparison of the binding behavior of analytes A'-D' to the sensor surface. For example, Figure 5 Strong binding signals from analytes A' and D' and weak binding signals from analytes B' and C' are shown.

[0108] However, the inventors have recognized that when more than one analyte is present, it would also be useful to determine how the analytes A'-D' interact with each other and / or with the ligands on the sensor surface. Such analysis may have particular application in the study of multiple analytes and ligands, and allow for new and insightful assays, as described in the implementations and examples below. However, it will be appreciated that when using the above and Figure 5 When using the method shown in , it is difficult to perform such an analysis because the first analyte will be removed, or at least significantly disturbed, by introducing a running buffer between samples. As will now be described, the currently disclosed system and method attempt to address this shortcoming.

[0109] In order to effectively analyze how first and second (and possibly more) analytes interact with each other, the present disclosure involves sequentially introducing first and second sample solutions (comprising first and second analytes, respectively), one after the other, without an intermediate running buffer flow. The inventors have recognized that, surprisingly, many assays can be effectively performed in this manner without requiring a running buffer flow between each sample injection. In fact, many assays and experiments benefit from the removal of running buffer flow between samples, as explained more fully below and demonstrated by the implementations and examples outlined below.

[0110] The sample injection process without an intermediate running buffer flow can be performed for multiple (i.e., two or more) sample solutions, and is referred to herein as a 'multi-injection' process as described above. To return to the above example of samples AD, the multi-injection process involves introducing each sample sequentially to the sensor surface without any intermediate running buffer flow. The response associated with such a method is Figure 6 Multiple injections are particularly useful because they allow interactions between analytes and ligands to be studied more efficiently. In particular, molecules that are sensitive to buffer flow can be studied without worrying about interreferences to the running buffer. Rapid interactions involving sequential injections of analytes can also be studied more efficiently because there is no 'down time' between sample injections due to running buffer flow.

[0111] The inventors have recognized that multiple injection procedures can be made more efficient by introducing gas segments between successive samples in a flow channel. Specifically, if multiple samples are injected into the same flow channel for delivery to a sensor surface, they will begin to mix as they flow through the channel, e.g. Figure 7a . The figure shows a first sample solution 502 including a first analyte and a second sample solution 504 including a second analyte, which flow through a first channel 506. At the interface of the two samples, mixing occurs. Once mixing begins, the analytes contained in the first and second samples will begin to react within the first channel 506, i.e., before the samples reach the sensor surface. When the samples reach the sensor, the interaction or reaction between the analytes may be partially or completely ended. Therefore, important reaction kinetics and characteristics may be missed because they have occurred before reaching the sensor surface and therefore cannot be analyzed.

[0112] To address this problem, a gas volume or gas segment can be introduced between successive sample solutions. This gas volume effectively forms bubbles in the flow channel, separating subsequent sample solutions and preventing mixing. This approach is Figure 7b 504, where a first sample solution 502 is separated from a second sample solution 504 by a gas section 503. This arrangement allows the two samples to pass through the first channel 506 and reach the sensor without mixing during transport. Only when reaching the sensor surface do the samples come into contact, at which point the interaction of the corresponding analytes can be analyzed.

[0113] Although Figure 7b The arrangement shown in enables multiple injections to be performed without worrying about premature mixing, but the inventors further recognized that it is undesirable to allow gas (e.g., gas segment 503) to contact the sensor surface. In particular, gas segment 503 may interfere with analytes from the first sample 502 that have been deposited at the sensor surface. In some instances, gas segment 503 may even cause damage to the sensor surface.

[0114] To address this problem, a second channel 508 may be provided near the end of the first channel 506, just before the sensor surface. Figure 8a-8c As shown in Figure 7b In the example of FIG. 5 , the process begins by introducing the first and second sample solutions 502, 504 into the first channel 506, and the samples are separated from each other by the gas segment 503. Then, the first sample solution 502, the second sample solution 504 and the gas segment 503 flow toward the sensor surface through the first channel 506. However, Figure 7b The arrangement is reversed, with the gas segment 503 being extracted from the first channel 506 via the second channel 508 before the gas segment 503 reaches the sensor surface. Figure 8b and ensure that the gas segment 503 does not contact the sensor surface. The second channel 508 can be routed directly to a waste reservoir, such as Figure 3 Storage 312.

[0115] Once the gas segment 503 has been extracted, the sample can be allowed to flow over the sensor surface, such as Figure 8c . The behavior of the sample at the sensor surface can then be analyzed. In particular, the binding of the analyte in at least one of the first sample 502 and the second sample 504 can be analyzed. This binding can be between the analytes in the two samples (i.e., one of the analytes can effectively act as a ligand by binding to the sensor surface and then capturing the second analyte), and / or between the analyte and a ligand that has previously been immobilized on the sensor surface. Alternatively, only the first sample solution 502 can include the analyte, and the injection of the second sample solution 504 can be used to change the environment (e.g., pH) in which the binding occurs, so that the behavior of the analyte under these new conditions can be studied.

[0116] Because the second channel 508 is located near the end of the first channel 506 where the fluid reaches the sensor surface, there is only minimal mixing between the first and second samples before reaching the sensor surface. Preferably, the gas segment 503 is removed no more than 40 seconds before the second sample 504 reaches the sensor surface. This time threshold ensures that the first and second sample solutions do not contact in the first channel 506 for a long enough time to cause significant mixing or interaction. Therefore, all or substantially all interactions between the sample solutions occur at the sensor surface and can therefore be analyzed. For rapidly dissociated analytes, the time between the gas segments 503 removed before the second sample 504 reaches the sensor surface may be no more than 30 seconds, no more than 20 seconds, no more than 10 seconds, or no more than 1 second. The time selected will depend on the analyte in question and can be determined by how much length of the first flow channel 506 is provided between the second flow channel 508 and the sensor surface.

[0117] Also refer to Figure 5 and Figure 6 When using a sample analysis system, it is often desirable to analyze the behavior of multiple analytes in succession. For example, a first set of samples A, B, C, and D may be analyzed. Sample A containing analyte A' is first injected. Analyte A' binds to the ligand on the sensor surface. The injection is followed by a flow of running buffer, during which some or all of analyte A' may dissociate, depending on the nature of the analytes. The process is then repeated for samples B, C, and D containing the corresponding analytes B', C', and D'. The response signals 5502, 5504, 5506, 5508 generated by the binding of analytes A'-D' are expressed in Figure 5Combined, these individual response signals provide a total combined signal 5500 for the assay of the four sample solutions. Note that the response signals are shown schematically and have simplified outlines. In practice, each combined response signal 5502-5508 will be similar to Figure 2 The response curves shown in and discussed above. Figure 5 The method shown in allows comparison of the binding behavior of analytes A'-D' to the sensor surface. For example, Figure 5 Strong binding signals from analytes A' and D' and weak binding signals from analytes B' and C' are shown.

[0118] exist Figure 5 In one implementation, running buffer is passed over the sensor between sample injections to keep the system properly wetted between samples. However, in other implementations, it may be preferred to omit the running buffer. In particular, the inventors have recognized that this may be desirable, for example, when analyzing rapid reactions where there is insufficient time for a running buffer step between analyte injections, or where it is necessary to accumulate fragile complexes on the sensor surface that may be disturbed by the running buffer flow. In these and other situations, the inventors have recognized that it may be beneficial to inject the samples sequentially, one after the other, without an intermediate running buffer flow. The process of injecting multiple (i.e., two or more) sample solutions without an intermediate running buffer flow is referred to herein as a 'multi-injection' process. To return to the above example of a collection of sample solutions AD, the multi-injection process involves introducing each sample sequentially to the sensor surface without any intermediate running buffer flow. The responses associated with such a method are described in detail in detail in the accompanying drawings. Figure 6 Here, the individual response signals 6602, 6604, 6606 and 6608 are again combined to give a total overall binding signal 6600 for the assay.

[0119] As mentioned, Figure 6 Multiple injections of this type as shown in are particularly useful because they allow a variety of interactions to be studied more efficiently. In particular, molecules that are sensitive to buffer flow can be studied without worrying about interference from the running buffer. Fast interactions involving serial injections of analytes can also be studied more efficiently because there is no 'down time' between sample injections due to running buffer flow.

[0120] Regardless of the method by which a set of samples is injected into the system, the result is an aggregate or total binding signal (or binding curve) for the set of samples, such as Figure 5 and Figure 6 The binding signal represents the binding response signal of each individual sample solution in the set of sample solutions (ie, including the combination thereof).

[0121] However, when analyzing a group of sample solutions, a problem arises in that existing methods make it difficult to determine which binding responses depend on or are affected by which other binding responses. It is also difficult to determine whether a binding response of one sample is masked by a larger binding response of another sample. For example, consider Figure 6 FIG. 6 shows a binding signal 6600 of FIG. 6601 . The signal includes four sub-signals 6602, 6604, 6606, and 6608, which are generated by samples AD (containing analytes A'-D'), respectively. Based on the binding signal 6600, it is possible to determine that there is binding of analytes from each sample AD at the sensor surface. It is also possible to determine that analyte A' has the largest binding response, while analyte C' has the smallest binding response. However, more complex analysis is difficult because it is difficult to know how the binding signals 6602-6608 are related to or interfere with each other. For example, it cannot be accurately determined whether each of analytes B', C', and D' is bound to a ligand or to another analyte. It is also impossible to accurately determine whether the dissociation signal of one analyte masks the association signal of a subsequently injected analyte, making it impossible to determine the true nature of the association of that analyte.

[0122] These problems may become more apparent by considering Figures 9 and 10, which show in more detail and in relation to more realistic binding signals how existing methods allow only limited analysis of combined binding signals. Once these shortcomings are discussed, improved methods to overcome the discussed problems will also be outlined in this disclosure.

[0123] First go to Figure 9a-9c , which show three binding signals 800, 900 and 1000. In this example, the binding signals 800, 900, 1000 are generated by injecting a set of sample solutions. Upon injection, the analyte arrives at the sensor surface and binds there, thereby generating an association response signal. Then, as the sample begins to be replaced by the subsequently injected sample, the initial analyte begins to at least partially dissociate, thereby generating a dissociation signal. The newly arrived analyte may begin to bind to the ligand, the analyte already present at the sensor surface, or neither. If binding occurs, the new analyte generates an association signal consistent with the dissociation signal of the first analyte.

[0124] As shown, in Figure 9a-9c In each of the assays shown in , the order in which the samples were injected was varied. Figure 9a In , the sequence is A, B, C. Figure 9b In , the sequence is B, A, C. This generates a different response signal 900. Finally, in Fig.9cIn , the sequence is B, C, A. This generates yet another response signal 1000. Due to the change in order, each binding signal has a slightly different profile. Regardless of the injection order, all three samples show binding.

[0125] According to Figure 9a-9c , it becomes apparent that binding signals 800-1000 provide only limited information. For example, it is known from these signals that binding occurs for each analyte regardless of the order of injection. While this information is useful as a starting point, it would be advantageous to have more detailed data regarding the exact response signals generated by each sample. Unfortunately, it is not possible to obtain this information from signals 800-1000 when using existing methods because the responses of the corresponding samples obscure each other. In particular, in Figure 9a , the dissociation signal of A is consistent with the association signal of B. Therefore, this "mixing" of the signals means that the true association signal associated with sample B is obscured and cannot be accurately determined. Similarly, the dissociation signal of B is consistent and therefore partially obscures the association signal of C. This means that it is difficult to obtain an accurate understanding of the association (or even dissociation) signal of any sample. Although in some cases it may be possible to obtain this data by performing an assay using only a single sample, in many cases, such as where the binding of one analyte (e.g., B') depends on the presence of another analyte (e.g., A'), this will not be possible. It is also impossible to determine from the signals 800, 900, 100 whether analytes A', B' and C' compete for binding sites.

[0126] Next go to Figure 10a-Figure 10b , another limitation of existing methods becomes apparent. Fig.10a A new binding response curve 1100 generated by sequential injection of different sets of sample solutions is shown. For simplicity, they are again labeled A, B, and C, and contain corresponding analytes A', B', and C', although it will be apparent that samples A, B, and C in the example of FIG. 10 are different from samples A, B, and C in FIG. 9. In the present example of FIG. 10, the assay involves the injection of a high concentration of 670 nM of a polyclonal antibody in sample A. Sample B contains a lower concentration of 10 nM of another antibody, while sample C contains a protein having a molecular weight of 25 kDa (100 nM), i.e., about one sixth of the antibody injected in the first two samples. Such an assay may be performed, for example, to analyze antibody-protein binding.

[0127] As can be seen, sample A generates a very large binding response, indicating that analyte A' is strongly bound to the ligand (or other capture molecule) at the sensor surface. In contrast, injections from samples B and C appear to yield little or no response. Even though Fig.10bA close-up of the graph shown in also reveals little - while there are slight 'ripples' in the responses when injecting B and C, the overall trend is still one of dissociation, i.e. a decrease in signal. This is because the dissociation response of sample A has obscured or 'swamped' the corresponding association responses of samples B and C. This behavior makes it difficult to determine any meaningful information about the behavior of samples B and C because they are so overshadowed by the response of A. This may occur, for example, when there are large differences in the molar ratios between the samples being analyzed. Figure 10a-Figure 10b In such cases, existing analytical techniques provide only limited information and the ability to analyze the sample's behavior.

[0128] As can be seen from the above explanation and consideration of Figures 9 and 10, existing sample analysis methods are unsatisfactory when analyzing the behavior of continuously injected samples. The present inventors have recognized a new advantageous method that addresses these shortcomings and allows for more complex and efficient analysis of various analyte binding interactions.

[0129] The realization of the improved method of the present disclosure is supported by the fact that by using continuous assays and subtracting the resulting binding signals, a wider variety of sample characteristics can be determined. This method is referred to as "cyclic subtraction" in the present disclosure. Now refer to Figure 11- Fig.17 Describes an example implementation of a loop subtraction method.

[0130] First go to Figure 11a-Figure 11c , showing the binding response curves implementing the cyclic subtraction procedure. Fig.11a A first binding signal 1200 is shown, resulting from sequential injections of three samples A, B, and C as part of a multiple injection assay.

[0131] The inventors have found that running a second assay using a buffer sample in place of one of the samples can achieve greater understanding and more efficient analysis of analyte behavior. As described above, a buffer sample solution is to be contrasted with a continuous running buffer flow. In particular, a buffer sample solution (or a sample of a buffer) comprises a specific volume of buffer provided via a sample injection pump or similar sample injection mechanism (usually from a sample bottle) in the same manner as any other sample solution. In the context of analyzing the analyte behavior at the sensor surface, the buffer sample is injected. This is in contrast to a running buffer flow, which is provided from a buffer reservoir by a buffer reservoir pump and whose sole purpose is to 'wash' and wet the system before or after performing an assay.

[0132] The second assay in this example involves sequential injections of sample A, buffer sample, and sample C. Thus, the second assay is similar to Fig.11aThe first assay was identical to that of , except that Sample B was replaced with a buffer sample, as shown below in Table 1. The buffer sample showed no response at the sensor surface due to the absence of the analyte contained therein.

[0133]

[0134] Table 1: Samples involved in the first and second assays that generated binding signals 1200 and 1300, respectively.

[0135] The second assay generates a second binding signal 1300, which is Fig.11b As shown in. By Fig.11a The first response signal 1200 is subtracted Fig.11b By analyzing the second response signal 1300, more understanding of the binding behavior of the analyte can be obtained. Fig.11c The resulting combined signal 1400 is shown in FIG. 1 , which can be considered as a third or difference signal. From this difference signal 1400, it is possible to Fig.11a At least two features of the binding response can be analyzed in a way that would not have been possible with the original binding signal 1200. First, the true form and magnitude of the response caused by sample B is now revealed. In the present case, Fig.11a The magnitude of the response in can now be determined more accurately because any ambiguous signal caused by the association and dissociation of A has been removed. Second, the binding response of both samples B and C can be seen in the difference signal 1400. This indicates that samples B and C are binding dependent. If sample B had independence with respect to sample C, then only the binding response of sample B alone would have been shown. However, Fig.11c The binding responses from both samples B and C are shown. More specifically, the difference signal 1400 shows that analyte C' binds only in the presence of analyte B'. This binding correlation is not apparent from the raw signal 1200, but is revealed by the cyclic subtraction method of the present disclosure.

[0136] Thus, as can be seen, the disclosed method not only enables more accurate analysis of a specific binding response (here the signal of sample B), but also enables uncovering binding correlations. Thus, more efficient sample analysis becomes possible.

[0137] Another example implementation of the disclosed cyclic subtraction method is shown in FIG. 12 . Fig.12a Shown with Fig.11a The same response signal 1200 is shown in FIG. 1 , which results from the sequential injection of samples A, B, and C.

[0138] Figure 12bA new response signal 1500 from a second assay is shown. The second assay in this example involves sequential injections of sample A, sample B, and a buffer sample. Thus, in this case, the second assay is again identical to the first assay, except this time sample C has been replaced with a buffer sample. The buffer sample exhibits no response at the sensor surface because it does not contain any analyte. Thus, the response signal 1500 is similar to Fig.11b The response signal 1300 is shown in Table 2, except that now sample C has been replaced with buffer:

[0139] assay Sample A Sample B Sample C Results Combination signal 1 A’ B’ C’ 1200( Fig.12a ) 2 A’ B’ Buffer samples 1500( Figure 12b )

[0140] Table 2: Samples involved in the first and second assays generating binding signals 1200 and 1500, respectively.

[0141] Fig.12c Again, the resulting combined signal 1600 generated by subtracting the second combined signal 1500 from the first combined signal 1200 is shown. Fig.11c The main benefit of calculating this difference signal 1600 is that the binding response of sample C can now be more accurately revealed because the ambiguous association and dissociation signals of samples A and B have been removed. The response signal 1600 only shows the binding response of sample C. However, from the binding signal 1400, it is known that sample C can only bind in the presence of sample B. Therefore, the observed binding signal 1600 for sample C is not independent, even though only the binding of C is shown in the graph 1600.

[0142] It is worth noting that from Fig.11c In the example above, we know that sample C depends on the presence of sample B. Therefore, injecting sample C by itself will not generate a signal. Therefore, when using the previous method, it is impossible to generate Fig.12c The binding signal shown in , where the binding signal of sample C is accurately separated from other signals and can be analyzed independently. In contrast, the new method currently disclosed makes it possible to analyze the signal response of sample C in detail.

[0143] Another example implementation of the disclosed cyclic subtraction method is shown in FIG. 13 . Fig.13a Again, it is shown that Fig.11a and Fig.12a The same response signal 1200 is shown in FIG. 1 , which results from the sequential injection of samples A, B, and C.

[0144] Fig.13bA new response signal 2300 resulting from a further sequential assay is shown. The sequential assay in this example involves injection of a buffer sample, sample B, and sample C. Thus, the sequential assay in this example is again identical to the first assay, except this time sample A is replaced with a buffer sample. The buffer sample exhibits no response at the sensor surface because it does not contain any analyte. Thus, the response signal 2300 is similar to Fig.11b The response signal 1300 and Figure 12b The response signal 1500 is as shown in Table 3, except that now sample A is replaced with buffer:

[0145] assay Sample A Sample B Sample C Results Combination signal 1 A’ B’ C’ 1200( Fig.13a ) 2 Buffer samples B’ C’ 2300( Fig.13b )

[0146] Table 3: Samples involved in the first and second assays that produced binding signals 1200 and 2300, respectively.

[0147] Fig.13c Again, the resulting combined signal 2400 generated by subtracting the second combined signal 2300 from the first combined signal 1200 is shown. Fig.11c and Fig.12c The main benefit of calculating this difference signal 2400 is that the binding response of sample A (specifically its dissociation curve) can now be more accurately revealed because the ambiguous association and dissociation signals of sample B and the ambiguous association signal of sample C have been removed. The response of sample A replicates that which would be expected from the binding of the analyte alone in isolation (note the difference with Figure 2 ). Also note that Fig.13c Repeated Fig.11b (where sample B had buffer in it, and sample C revealed no binding), again indicating the presence of sample A independent of sample B and sample C.

[0148] Turning now to additional examples, in which the disclosed methods allow for improved analysis, Fig.14a Shown with Fig.10a 1100. As previously described, due to the large difference in molar ratios, the response of sample A dwarfs the responses of samples B and C, making the responses of samples B and C almost indistinguishable. However, by using the presently disclosed method, i.e., by performing cyclic subtraction in the manner described above, additional insight into the behavior of B and C can be gained.

[0149] To achieve this, in this example, two additional assays were performed as shown in Table 4.

[0150] assay Sample A Sample B Sample C Results Combination signal 1 A’ B’ C’ 1100( Fig.14a / b) 2 Buffer samples B’ C’ 1100a( Fig.14a / b) 3 A’ B’ Buffer samples 1100b( Fig.14a / b)

[0151] Table 4: Samples involved in the first, second and third assays that generated binding signals 1100, 1100a and 1100b respectively.

[0152] First, the assay is repeated, but with the buffer sample replacing sample B. This generates a binding signal 1100a. Then, the assay is repeated again, but with the buffer sample replacing sample C. This generates a binding signal 1100b. Because these signals are very similar to each other and to the original signal 1100, all three signals are shown in Fig.14a on the same plot in . Fig.14b A close-up of the segment during which samples B and C were injected is shown. Fig.14b Equivalent to Fig.10b , except that now also the binding signals for the second and third assays are shown.

[0153] Now, by using cyclic subtraction, the behavior of samples B and C can be efficiently studied, as Fig.14c and 14d First go to Fig.14c , subtracting binding signal 1100a (buffer sample as sample B) from raw binding signal 1100 generates a first differential binding signal 1700. As can be seen, the obscuring "noise" from the dissociation of sample A is now largely removed, and the association signal due to analyte B' can be accurately determined. In particular, the upward association curve that was previously obscured by the downward dissociation signal of sample A can now be seen and analyzed.

[0154] Similarly, Fig.14d A second differential binding signal 1800 is shown which is generated by subtracting the binding signal 1100b (the buffer sample is taken as sample C) from the original binding signal 1100. Fig.14c In the case of , the obscuring "noise" from the dissociation of sample A is now largely removed, and the association signal due to analyte C' can be accurately determined. In particular, the upward association curve that was previously obscured by the dissociation signal of A can now be seen and analyzed.

[0155] Thus, as can be seen, the disclosed methods enable previously hidden binding signals to be accurately revealed and analyzed.

[0156] Another important area where the disclosed methods provide benefits is in the process of "epitope binning". This involves determining which epitopes (e.g., epitopes of an antigen) an analyte (e.g., an antibody) binds to. During drug development and antibody screening, it is important to understand how antibodies interact with antigens, particularly whether two or more antibodies compete for a single antigenic epitope. By the disclosed methods, such analysis is made significantly simpler, as will now be explained.

[0157] A first example of such an epitope binning analysis will initially be described with reference to FIG. 15 . Fig.15a An example binding complex that may be formed at the sensor surface during a particular assay is shown. Anti-mouse antibody (α-mouse) is immobilized at the sensor surface to act as a ligand. Three samples A, B, and C are then injected consecutively in the manner described above. In this example, the first sample solution A contains the first antibody of interest Ab1. The second sample solution B contains the antigen (Ag). Finally, the third sample solution C contains the second antibody of interest Ab2.

[0158] In many cases, it is desirable to determine whether antibodies Ab1 and Ab2 bind to antigen Ag in the presence of each other. Such an analysis can determine whether Ab2 and Ab1 compete for the same epitope (binding site) on the antigen, which can inform drug discovery and antibody screening studies as described above. Unfortunately, analysis of this interaction is difficult using existing methods because Ab2 in this example (and in many other 'real world' examples) also binds to a ligand (α-mouse in this example). This second binding opportunity available to Ab2 is determined by Fig.13a Indicated by the arrow in . Therefore, when sample C containing Ab2 is injected, there will be a binding response signal, but it will be impossible to know how much of this signal is caused by binding between Ab2 and antigen Ag, and how much is caused by Ab2 binding to an empty binding site at the α-mouse ligand. In other examples, binding between the two antibodies may occur and produce another "noise" signal that obscures the signal of interest between Ab2 and antigen.

[0159] Traditionally, this problem has been addressed by using so-called "blocking" molecules to block any empty binding sites (e.g., sites on the ligand) prior to injection of the Ab2. Once such a blocking molecule is added, the Ab2 has no binding site at the ligand to bind to, and therefore once the Ab2 is injected, there is no unwanted "noise" signal caused by such binding. The magnitude of the binding between the Ab2 and the antigen Ag can then be accurately determined.

[0160] Unfortunately, however, developing an assay that includes such a blocking molecule is time-consuming and difficult. Suitable blocking molecule candidates must be identified and tested. Typically, blocking candidates exhibit poor performance and are not as effective as expected in theory, which means that a large number of candidates must be tested frequently. In practice, even in a complex laboratory setting, this may take weeks or months. This creates a great obstacle to performing a large number of assays, because research must be conducted before each assay to find a suitable blocking molecule.

[0161] As will now be described, the presently disclosed cyclic subtraction method enables analysis without the need for blocking molecules. Fig.15aThis provides significant benefits and makes large-scale analysis more feasible as the need to first identify a suitable blocking molecule is removed.

[0162] As in the above implementations, this example implementation begins with the injection of a first set of sample solutions A, B, and C, which in this example contain analytes Abl, Ag, and Ab2, respectively. This results in the formation of Fig.15a The complex shown in Fig.15b The first binding signal 1900 shown in . As in other implementations of the disclosed method, the assay is then repeated using a subset of the sample solution and a buffer sample. In this example, in the second assay, the antigen Ag is replaced with a buffer sample, as shown in Table 5:

[0163] assay Sample A Sample B Sample C Results Combination signal 1 Ab1 Ag Ab2 1900( Fig.15b ) 2 Ab1 Buffer samples Ab2 2000( Fig.15c )

[0164] Table 5: Samples involved in the first and second assays generating binding signals 1900 and 2000 respectively.

[0165] The second assay generates a second binding signal 2000, Fig.15c As previously described, the disclosed method then involves subtracting the binding signal 2000 from the binding signal 1900. This cyclic subtraction removes any 'noise' caused by binding between Ab2 and the ligand on the sensor surface (or actually from binding between Ab2 and Abl, if such binding occurs), leaving only the binding of interest, i.e., the binding between Ab2 and Ag. The resulting difference binding signal 2100 is shown in Figure 13d. As can be seen, in this case, even once any Ab2-ligand binding has been subtracted, there is still a clear association signal for sample C. This shows that even in the presence of Ab1, there is binding between Ab2 and antigen Ag, which means that Ab2 and Abl do not compete for the same epitope of Ag. Crucially, this useful understanding is obtained without the need for blocking molecules, representing a significant improvement over existing methods for studying epitope competition.

[0166] It will be appreciated that the above examples are intentionally simplified to aid understanding. All methods disclosed herein can be applied to more complex assays involving a greater variety of analytes of interest. One such example is Fig.16a , which shows a plurality of differential response signals obtained by cyclic subtraction in the above manner. Specifically, these signals show the results from an epitope binning experiment, which includes three antibodies (respectively labeled 1277, 1285 and 1290) and the antigen human creatine kinase (CKMB). A more detailed example setup for performing such an experiment is described in Example 2 below.

[0167] The antibodies were analyzed in pairs, two at a time. Samples were injected and analyzed, and then the antigen was replaced by a buffer sample in a sequential assay in the same manner as described above with reference to Figures 11-15. This process was repeated with each antibody pair and with the antibodies injected in a different order, as shown in Table 6 below.

[0168]

[0169]

[0170] Table 6: Samples involved in the eighteen assays performed to study epitope competition in epitope binning analysis between three antibodies

[0171] The binding signal obtained from the even-numbered assay (involving the buffer sample) is subtracted from the binding signal of the previous odd-numbered assay via cyclic subtraction as described above. For example, the binding signal generated by assay 2 is subtracted from the binding signal generated by assay 1. Assay 4 is subtracted from assay 3, and so on. This cyclic subtraction generates nine different binding signals, which are Fig.16a Shown in.

[0172] From these signals, it is possible to determine which antibodies compete for the same epitope and how the ordering affects competition. The assumption is that with two injections of the same antibody, there will be epitope competition because antibodies naturally compete with themselves. Therefore, any differential signal below the highest self-competition signal (1277 / 1277 in this example) is considered to be indicative of epitope competition. The "Epitope Competition" area in the graph is Fig.16a As can be seen, all but four of the antibody combinations competed with each other. The results are also schematically shown in Fig.16b , where the grey segments represent epitope competition and the white segments represent no competition. The left hand column shows the first antibody injected in the assay and the top row shows the second antibody injected. Thus, the table indicates that no matter what order the antibodies are injected, there is no competition between analytes 1285 and 1277. The same is true for antibodies 1285 and 1290, although Fig.16a It can be noted in the graph of 1290 / 1285 that the 1290 / 1285 difference curve is close to the 1277 / 1277 cut-off. This may indicate that further study of the 1290 / 1285 interaction may prove to determine why the binding response may be weaker when the antibodies are injected in this order. All other combinations and orders of antibodies in this example result in epitope competition (i.e., in this example, falling at or below the 1277 / 1277 cut-off). It will be appreciated that in other examples, antibodies may exhibit unidirectional competition, i.e., competition that depends on the injection order.

[0173] It should be emphasized that all of this information about epitope competition has been and can be obtained by analyzing only using three antibodies, antigens and buffer samples and performing cyclic subtraction in the above-disclosed manner. It is not necessary to utilize blocking molecules to block free ligand binding sites because any unwanted binding signals between antibodies and ligands are removed by cyclic subtraction methods. Any number and combination of antibodies can be assayed and studied in this way. This presents a significant improvement relative to existing methods that rely on the use of blocking molecules.

[0174] Fig.16c Results from a similar experiment are shown, however in this case a lower ligand density was used on the surface (approximately 1000 RU compared to Fig.16a As can be seen, the same results were repeated regarding which antibodies competed. The fact that the same results were obtained regardless of ligand density shows the robustness of this method.

[0175] Fig.17 The above-described cyclic subtraction method for assaying multiple sets of sample solutions is summarized in . At block 1402, a first set of sample solutions including at least three sample solutions is provided. Typically, although not necessarily, the sample is aspirated and injected into a flow channel configured to deliver the sample to the sensor surface. At block 1404, an assay is performed using the first set of sample solutions, during which each sample solution in the first set of sample solutions is sequentially flowed over the sensor surface. This generates a first binding signal 1406.

[0176] Next, a second set of sample solutions is provided at frame 1408. The second set of sample solutions includes a subset of the first set of sample solutions and a buffer sample solution. In other words, at least one sample solution in the first set of sample solutions provided at frame 1402 has now been replaced by a buffer sample. At frame 1410, an assay is performed using the second set of sample solutions, during which each sample solution in the second set of sample solutions flows sequentially over the sensor surface. This generates a second binding signal 1412. Then, at frame 1414, the second binding signal 1412 is subtracted ("cyclic subtraction") from the first binding signal 1406. This generates a third (difference) binding signal 1416.

[0177] When using the multiple injection approach, many of the above implementations as well as Fig.17 The method generally provides particular utility in that samples are injected sequentially without intermediate running buffers or any "down time" between samples. In such implementations, the inventors have recognized a number of additional optional features that may be used to improve the effectiveness of the assay.

[0178] One such feature involves the use of gas segments to separate consecutively injected samples. The inventors have recognized that the multiple injection process can be made more efficient by introducing gas segments between consecutive samples in the flow channel, as described above with respect to FIGS.

[0179] Fig.18 A method combining the above steps is shown in . The method involves providing and extracting gas segments, but it will be appreciated that these steps can be omitted in some cases, particularly where the first flow channel is short enough that mixing is negligible, or where the interaction is such that the effects of mixing of the solutions before reaching the sensor are minimal. However, in most cases, avoiding mixing in the first channel will enable more efficient analysis of sample interactions.

[0180] Fig.18 The method involves introducing a first sample solution into a first channel (e.g., channel 506 of the analysis system 300) at block 1702. Figure 8a-8c As shown in , the first channel is configured to deliver the sample solution to the sensor surface. At block 1704, the second sample solution is introduced into the first channel. As described above, this example implementation involves the use of a gas segment. Therefore, as described above with reference to Figure 7b and Figure 8a As described above, the second sample solution passes through the gas section in the first channel to be separated from the first sample solution. The gas section prevents the samples from mixing in the first channel.

[0181] At box 1706, the first sample solution, the second sample solution, and the gas segment flow toward the sensor surface through the first channel. This flow is usually performed under the action of a first pump of the analysis system, which is configured to flow the sample through the first channel toward the sensor surface and over the sensor surface. Before the gas segment reaches the sensor surface, at box 1708, the gas segment is extracted from the first channel via the second channel. This ensures that the gas segment does not contact the sensor surface. As described above, box 1708 preferably occurs at most 40 seconds before the second sample solution reaches the sensor surface to ensure that any mixing and interaction between the first and second sample solutions in the flow channel (i.e., before reaching the sensor surface) is negligible for the purpose of analysis.

[0182] At block 1710, a first sample solution and a second sample solution are flowed over a sensor surface so that they can interact with each other and / or with ligands already provided at the sensor surface. Fig.18 Block 910 is shown after block 908 in FIG. 1 , but when block 1708 (the extraction gas phase) occurs, some of the first solution may already be present at the sensor surface. This Figure 8b, wherein when the gas extraction section 503 is performed, the first sample solution 502 has partially contacted the sensor (not shown, but present in Figure 8b to the right of the first flow channel 506).

[0183] At block 1712, the interaction behavior of the first and second samples at the sensor surface is analyzed, and in particular, the presence or absence of binding of an analyte from at least one sample solution is detected at the sensor surface.

[0184] Advantageously, throughout Fig.18 Methods without running buffer solution (e.g. from Figure 3 The running buffer reservoir 308 of the sensor surface is passed over the sensor surface, i.e., until the interaction of the sample solution has been completed to a sufficient extent, wherein the desired analysis has been performed. Once the analysis (or interaction) is completed, the running buffer can enter the system to clean the sensor surface and prepare the system for a new assay.

[0185] Will understand, Fig.18 The method can be implemented using more than two sample solutions, wherein each sample solution is preferably separated from the previous sample solution by a corresponding gas segment. Fig.18 The method may optionally modify one or more characteristics in each successive repetition. For example, as described above, the order in which the samples are injected and / or the environment in which the interaction occurs (e.g., pH, concentration) may be changed.

[0186] The above-described methods open up a wide range of potential applications and analyses, as will now be described in the following implementations and examples, which provide a non-exhaustive list of applications to which the disclosed multiple injection and cyclic subtraction methods and systems may be applied.

[0187] accomplish

[0188] Provided below is a list of implementations where the inventors have recognized that the disclosed methods and systems may be particularly beneficial. It will be understood that this list is not exhaustive and that the disclosed methods and systems may find utility in other implementations and contexts.

[0189] · Revealing hidden binding signals and epitope binning: As described in detail above, the disclosed cyclic subtraction method enables revealing hidden binding signals and removing unwanted "noise" from other association or dissociation signals. Epitope binning is also facilitated, where competition between antibodies for antigen binding sites is analyzed. The achievement of this will be described more fully below in Example 2.

[0190] Complex formation: The present methods and systems enable the construction of complex formation at the sensor surface for more efficient analysis. For example, analytes in the first and second sample solutions may bind to each other to form a complex formation (e.g., a complex bound to an antibody) or a cascade reaction (e.g., a blood coagulation cascade). Such complexes may be unstable and weakened or rapidly dissolved in the presence of a running buffer. Existing methods that allow the running buffer to flow and extend the time between samples (e.g., Figure 5 The method shown in ( ) is therefore not suitable for effectively performing these analyses. The currently disclosed method achieves sufficiently fast formation and analysis of complexes without degrading complex formation. This implementation is described more fully in Example 1 below.

[0191] ● Revealing hidden binding signals and epitope binning: In addition, sequential assays involving subsets of sample solutions can be performed to reveal previously hidden binding properties. For example, a first assay involving a first set of sample solutions including three or more sample solutions can be performed to obtain a first binding signal. A second assay involving a subset of the first set of sample solutions and a buffer sample can then be performed to obtain a second binding signal. A differential binding signal can then be obtained by subtracting the second binding signal from the first binding signal. The differential binding signal can reveal previously hidden binding properties and interactions, and can also be used to identify whether analytes (e.g., antibodies) bind to the same or different epitopes (e.g., epitopes of an antigen) from each other. This implementation is described more fully below in Example 2.

[0192] Analyzing ligand properties: The present methods and systems enable more efficient analysis of ligand behavior in the presence of a variety of analytes and environments at the sensor surface. For example, the binding of analyte(s) to the ligand in the presence of successive sample solutions with different pH values ​​can be studied. This can also allow ligand conformation, refolding, and stability properties to be more easily studied.

[0193] Preparation of different lipid environments: The present methods and systems enable more efficient analysis of lipid behavior on a sensor surface. For example, a first sample solution may include a membrane protein captured on a sensor surface (e.g., by a ligand). A second sample solution may include lipids configured to cover the membrane protein. This behavior can be studied without any running buffer that may interfere with the membrane protein.

[0194] Denaturation / renaturation experiments: The present methods and systems enable more efficient analysis of the denaturation and renaturation of ligand proteins and nucleic acids (e.g., DNA and RNA) on sensor surfaces. In particular, interactions involving rapid switching between denaturation and renaturation conditions on the surface can be studied since there is no 'down time' to inject running buffer flow between samples.

[0195] · Fast Interactions: For similar reasons, the present methods and systems enable more efficient analysis of fast interactions on sensor surfaces. Examples include enzyme-substrate reactions that can occur in as little as 1 μs. In these contexts, the disclosed methods can provide an alternative to so-called stopped-flow experiments, which have rapid introduction and removal of enzyme substrates, cofactors and products, which are provided to affect the stability of the binding of molecules on the sensor surface. For similar reasons, analytes that naturally dissociate rapidly can also be studied more effectively. Such fast-dissociating samples can also be locked to the sensor surface in a procedure called 'docking and locking', whereby the sensor surface is activated by reagents before the introduction of ligands and analytes. In this case, the time between the activation injection and the ligand injection may be critical. The methods and systems of the present invention also facilitate similar implementations involving cross-linking of ligands through multi-step chemistry. Other examples of fast interactions include amine coupling, where the activation of the sensor chip surface typically decays over time. The currently disclosed methods and systems allow for faster assay run times, resulting in an increase in the level of immobilization to alleviate this situation. Each of the above is facilitated by the disclosed methods and systems, which enable efficient analysis of rapid interactions.

[0196] Antibody studies: The present methods and systems enable more efficient analysis of the interactions of antibodies on the sensor surface. In particular, several antibodies can be injected sequentially and the behavior of each antibody studied. This can reveal how a given receptor interacts with different antibodies.

[0197] Lock-in experiments: By alternating injections of samples containing analyte and samples containing buffer, frequency analysis (e.g. Fourier transform) can be used to assess kinetics. This allows low signals (close to measurement noise) to be detected and used for analysis. By varying the duration / volume of successive buffer samples (or buffer 'pulses'), kinetics can also be assessed.

[0198] Analysis of sensitive analytes: Some samples are incompatible with running buffer and therefore cannot be effectively studied using traditional methods where the running buffer flows before and after each sample injection. Examples of such sensitive analytes include metal ions of precipitating buffer substances and cofactors. The present methods and systems enable more efficient study of such sensitive analytes on the sensor surface. For example, the sensitive substance can be protected by injecting other solutions before and after the sensitive solution. In this way, the sensitive analyte is protected from the running buffer flow and can be effectively studied.

[0199] - Agonists and Antagonists: The present methods and systems enable more efficient analysis of agonists and antagonists on a sensor surface, for example by sequentially injecting antagonists or agonists to map their behavior.

[0200] It will be appreciated that one or more of the above-described implementations may be combined to provide other useful implementations and applications of the disclosed systems and methods.

[0201] Example

[0202] The following non-limiting examples set forth two example implementations of the disclosed methods and systems in greater detail.

[0203] 1. Complex Formation

[0204] i. The in-house produced ligand RBD (receptor binding domain, SARS-CoV-2) was diluted from 2.53 mg / mL to 5 μg / mL using 10 mM sodium acetate, pH 4.5.

[0205] ii. Ligands are coupled to the sensor chip CM5 Cytiva Amine via pre-programmed settings for use in the Cytiva Amine Coupling Kit using reagents. Standard immobilization was performed on the system. The ligand was injected for 7 minutes, resulting in an immobilization level of 895RU. The running buffer was HBS-EP+ from Cytiva. In all assays, HBS-EP+ from Cytiva was used as the running buffer and in the buffer samples.

[0206] iii. Analyte Dilution: A first analyte, ACE2 (angiotensin converting enzyme-2) stock solution produced in-house, was diluted from 1.1 mg / mL to 0.056 mg / mL using buffer to provide a first sample solution. A second analyte, anti-RBD (clone CR3022) antibody from lifeSpan BioSciences, was diluted from 1 mg / mL to 1.5 μg / mL using buffer to provide a second sample solution. A third analyte, anti-human IgG (Fc) from Cytiva, was diluted from 0.5 mg / mL to 1.5 μg / mL using buffer to provide a third sample solution.

[0207] iv. The three sample solutions were sequentially injected into the flow cell using a multi-inject 3-segment command without any running buffer flow between the corresponding samples. A gas segment was set between each sample solution in the flow cell to prevent mixing. Each gas segment was extracted shortly before reaching the sensor surface via another flow channel. The contact time for each sample injection was 120 s and the flow rate was 30 μL / min. After the injection of the three samples, the dissociation time was 180 s. The sensor chip was regenerated using 10 mM glycine-HCl at pH 1.5 from Cytiva, and the regeneration solution was used after each contact time of 30 seconds.

[0208] v. Obtaining a binding response signal from the assay, reflecting the binding interactions at the sensor surface involving the first, second, and third analytes. The binding response signal is suitable for use in complex formation analysis to determine how the samples interact at the surface, and in particular to determine whether the binding of any analyte is dependent on the presence of any other analyte.

[0209] vi. Repeat the assay using a subset of the sample solution from the first assay and a buffer sample solution. In this example, in the second assay, the sample solution containing anti-RBD (clone CR3022) is replaced by a buffer sample. The result binding signal is subtracted from the initially obtained binding signal to give a difference signal, thereby revealing the true binding properties of anti-RBD (clone CR3022) and identifying any associated correlation or independence in the binding. Then a third assay is performed, in which the sample solution buffer sample containing anti-human IgG is replaced. The result binding signal is subtracted from the initially obtained binding signal again to give a difference signal, thereby revealing the true binding properties of anti-human IgG and identifying any associated correlation or independence in the binding. Then a fourth assay is performed, in which the sample solution containing ACE2 (angiotensin converting enzyme-2) is replaced by a buffer sample. The result binding signal is subtracted from the initially obtained binding signal again to give a difference signal, thereby revealing the true binding properties of ACE2 (angiotensin converting enzyme-2) and identifying any associated correlation or independence in the binding.

[0210] 2. Epitope Binning

[0211] i. Mouse antibody capture kit antibody from Cytiva was diluted from 1 mg / mL to 30 μg / mL using 10 mM sodium acetate (pH 5.0) and amine coupled to sensor chip CM5 using reagents in the amine coupling kit from Cytiva. Pre-programmed settings for standard fixation and low fixation on the BIACORE system were used for fixation, i.e., the contact time of EDC / NHS was 7 min and 30 s, respectively. The reference flow cell was not treated. The fixation process of high ligand density, i.e., injection of EDC / NHS7 min, produced 8657 RU, and the fixation process of low ligand density, i.e., injection of 60 s, produced 1007 RU. HBS-EP+ from Cytiva was used as running buffer and sample buffer in all assays.

[0212] ii. The antigen stock solution (human creatine kinase (CKMB) from BioSpacific) was diluted from 1 mg / mL to 4.3 μg / mL using a buffer to provide a first sample solution.

[0213] iii. Monoclonal mouse antibodies (mAbs) produced in-house against CKMB 1277, 1290, and 1285 were diluted to a final concentration of 100 nM using buffer to provide second, third, and fourth sample solutions.

[0214] iv. Use the multi-injection 3-segment command to inject samples of three of the four preparation solutions into the flow cell in various orders, and there is no running buffer flow between different samples, as shown in the table below. A gas segment is provided between each sample solution in the flow cell to prevent mixing. Each gas segment is extracted shortly before reaching the sensor surface via another flow channel. Each antibody is tested for each antibody itself and for each other antibody. For each assay, a continuous assay is performed using a buffer sample to replace the antigen. This results in a total of eighteen assays for each antibody pair, as shown in Table 7 below. The contact time for each sample injection is 120s and the flow rate is 20μL / min. In each assay, the injection of three samples is followed by a dissociation time of 30s. After each assay, the sensor chip is regenerated with 10mM glycine-HCl pH 1.7 from Cytiva.

[0215] assay Sample A Sample B Sample C 1 1277 CKMB 1277 2 1277 Buffer samples 1277 3 1277 CKMB 1285 4 1277 Buffer samples 1285 5 1277 CKMB 1290 6 1277 Buffer samples 1290 7 1285 CKMB 1285 8 1285 Buffer samples 1285 9 1285 CKMB 1277 10 1285 Buffer samples 1277 11 1285 CKMB 1290 12 1285 Buffer samples 1290 13 1290 CKMB 1290 14 1290 Buffer samples 1290 15 1290 CKMB 1285 16 1290 Buffer samples 1285 17 1290 CKMB 1277 18 1290 Buffer samples 1277

[0216] Table 7: Eighteen assays performed for each antibody pair to study epitope competition.

[0217] v. Obtaining a binding response signal from each assay that reflects the binding interactions at the sensor surface involving the first, second, and third samples in the corresponding assay. Fig.16a As described above, the binding response signals are subtracted from each other to generate nine different binding signals, similar to Fig.16a The binding signals are those shown in . These binding signals enable determination of whether the corresponding antibodies compete for the same epitope of the antigen. It has been determined that antibodies 1290 and 1277 always compete, while antibodies 1277 and 1285 and 1285 and 1290 do not compete.

[0218] Variants

[0219] The above detailed description describes a variety of example arrangements and methods for delivering a sample solution to a sensor surface of a biosensor. However, the arrangements and methods described are merely exemplary, and those skilled in the art will appreciate that various modifications may be made without departing from the scope of the appended claims. Some of these modifications will now be briefly described, however this list of modifications is not considered to be exhaustive, and other modifications will be apparent to those skilled in the art.

[0220] More generally, it should be appreciated that the number of steps and features shown in the figures is not limiting. Steps may be repeated as often as desired, and certain steps and features may be omitted.

[0221] In many of the above examples, a first assay is performed, followed by a continuous assay. The binding curve of the continuous assay is then subtracted from the first assay. It will be appreciated that this assay order is included only for ease of understanding and may be changed. For example, a first assay may be performed, followed by a second assay. The binding signal of the first assay may then be subtracted from the binding signal of the second assay. That is, it is not required that the second assay always subtracts the assay whose binding signal is to generate a differential signal. Instead, the only requirement is to perform an assay with a set of sample solutions, and then perform another assay using a subset of the sample solutions and a buffer sample. The binding signal from the subset+buffer may then be subtracted from the binding signal of the complete set of samples. The order in which the assays are performed is not important.

[0222] The above examples refer primarily to "injecting" a sample into a flow channel of a biosensor system. In particular, in a preferred arrangement, the first and second sample solutions are aspirated from respective first and second sample solution reservoirs and injected into the first channel for delivery to the sensor surface. However, it will be appreciated that this mechanism is non-limiting and that the sample may be introduced into the system in any suitable manner, such as by suction or other forms of pressure that pushes or draws the sample solution from its sample bottle or reservoir into (one or more) suitable flow channels.

[0223] Similarly, the movement or flow of the sample solution through the flow channel of the system is usually controlled by one or more fluid flow pumps. In the example arrangement, each flow channel (e.g., the first and second flow channels discussed above) operates under the action of a corresponding pump. In this case, the sample is drawn (or pushed) through the first channel by the first pump, and then at the appropriate moment, drawn (or pushed) through the second channel by the second pump, so that the gas segment can be removed. After removing the gas segment, the first pump can take over again to deliver the sample solution to the sensor surface. Although this arrangement provides particularly accurate control of fluid flow, it will be appreciated that any suitable arrangement for making the sample solution flow through a suitable flow channel can be used, such as any suitable arrangement of pumps, valves, pistons, and actuators.

[0224] The above examples described how to provide running buffer from a running buffer reservoir using a running buffer pump. It will also be appreciated that any suitable arrangement of pumps, valves, pistons and actuators may be used to deliver running buffer from a running buffer reservoir to the system.

[0225] As described above, before the analyte is injected, the sensor surface can be fixed with a ligand. In this case, the binding of the analyte to the ligand in the first and second (and possibly more) sample solutions can be analyzed. Alternatively, the first and second sample solutions can be injected without pre-fixing the ligand on the sensor surface. In this case, as described above, the analyte in the first sample solution is usually combined with the sensor surface and effectively acts as a ligand, and once the second sample solution also reaches the surface, the analyte is captured from the second sample solution. However, for ease of understanding, the term 'ligand' refers to a molecule introduced and fixed to the sensor surface in this article, and its only purpose is to act as a fixed interactor, rather than an analyte that measures its binding response. In some examples, the first sample may include a sensor preparation solution (e.g., an activation reagent), and the second solution may include a ligand to be attached to the activated sensor surface.

[0226] The above description uses the example of introducing a first sample and then introducing a second sample. It will be appreciated that in many cases, it will be useful to repeat the process using one or more modified parameters. For example, the order in which the samples are introduced can be changed (e.g., sample A then B, followed by sample B then A). Alternatively / additionally, the environment in which the samples are introduced can be changed. For example, the pH value of one or more samples can be changed so that the effect of pH on the reaction can be analyzed. Similarly, the concentration of at least one sample can be changed so that the effect of analyte concentration on the reaction can be analyzed.

[0227] Although the above description focuses on the routine that each sample solution includes the analyte of interest, one or more sample solutions may alternatively or additionally include a buffer solution, a washing solution, or a sensor surface regeneration solution. By introducing these fluids as sample solutions, the operator has more control than when using, for example, a continuous running buffer flow from a running buffer reservoir, which typically manages an unspecified or uncontrolled amount of buffer. Providing these solutions as sample solutions allows discrete, highly controlled volumes of fluid to be provided to the sensor surface as part of the analysis to meet certain functions as part of the analysis, such as shown in Example 2 above. As described above, it is emphasized that the buffer sample is different from the running buffer because the buffer sample is provided from a sample reservoir (such as a vial or microplate) and is injected into the system in the same manner as any other sample solution. It has a discrete, highly controlled volume and is injected for the purpose of analyzing the behavior of the analyte at the sensor surface, such as shown in Example 2 above. In contrast, the running buffer is provided from the running buffer reservoir via a different mechanism (e.g., via a discrete running buffer pump), and the purpose is to rinse off the analyte at the end of the assay and keep the instrument wet when there is no sample flow.

[0228] The volume of sample solution provided can be determined based on the desired (or target) duration during which the sample is intended to be present on the sensor. The volume can be determined using the following formula:

[0229] Volume = flow rate * time

[0230] Where volume is the volume of sample solution introduced into the system, flow rate is the rate at which the sample solution passes through the sensor surface, and time is the target duration that the sample solution is present at the sensor surface. For example, if the desired time at the sensor is 1 second, and the flow rate is 100 μl per second, then it can be determined that the required volume of sample that needs to be injected is 100 μl.

[0231] The methods discussed above are primarily presented in the context of SPR. However, it will be appreciated that any biosensor system having a sensor surface over which a sample solution can flow and at which binding events can be detected is suitable for the disclosed methods. Such a biosensor may, for example, be based on evanescent wave sensing or another optical or non-optical mechanism for detecting binding or reaction events at the sensor surface.

[0232] When a gas segment is provided between samples and extracted, it is preferred to extract a gas segment close enough to the second solution that reaches the sensor surface so that any mixing that occurs after the gas segment is removed can be ignored. For example, in an implementation where the first and second sample solutions are separated by the gas segment, the first sample solution can contact the sensor surface during a first time period, and the second sample solution can contact the sensor surface during a second time period. The first and second time periods can be referred to as the 'contact time' of the first and second samples. The delay between the end of the first time period and the beginning of the second time period (i.e., the gap between the two contact times) is preferably 40 seconds or less. This time threshold ensures that the disclosed method is suitable for analyzing interactions involving analytes that dissociate or degrade rapidly. For example, the first injected analyte in the first sample may bind to the sensor surface, but then dissociate quickly. Ensuring that the second sample arrives within 40 seconds or less ensures that for a wide range of implementations, the second sample will arrive at the sensor in time before the first analyte dissociates to allow the interaction of interest to occur. More preferably, the delay between the first and second samples is 30 seconds or less, 20 seconds or less, 10 seconds or less, or 1 second or less. These successively shortened time periods ensure that even very rapidly dissociating analytes can be analyzed. This time range is possible with the methods and systems disclosed herein because there is no 'down time' due to intermediate run buffer injections. For example, the exact time between the first and second samples arriving at the sensor can be determined by the length of the flow channel through which the samples flow between gas segment extraction and the sensor. The disclosed methods and available time ranges between samples mean that the assay environment can be developed around and modified to suit a specific analyte of interest.

[0233] Computer Systems

[0234] Finally go to Fig.19 , Fig.19 A schematic and simplified representation of a computer device 1801 is shown, which can be used to perform the methods described herein alone, in combination with other computer devices, or as part of a 'cloud' computing arrangement. For example, the computer device 1801 can form part of the analysis system 300, or be connected (wirelessly or via a wired connection) to the analysis system 300, and can be configured to cause the analysis system 300 to perform various methods disclosed herein. The computer device 1801 can also perform analysis on readings or information generated by sensors of the analysis system 300.

[0235] Computer equipment 1801 in the illustrated example includes various data processing resources, such as a processor 1802 (specifically a hardware processor) coupled to a central bus structure. Also connected to the bus structure are data processing resources, such as a memory 1804. Display adapter 1806 connects display device 1808 to the bus structure. One or more user input device adapters 1810 connect user input devices 1812 such as keyboards and / or mice to the bus structure. One or more communication adapters 1814 are also connected to the bus structure to provide connections to other computer systems 1801 and other networks. Computer equipment 1801 can be a local computer or server. It can be an independent element, or it can be a part of the existing computer hardware used for sample analysis laboratories.

[0236] In operation, the processor 1802 of the computer system 1801 executes a computer program including computer executable instructions that may be stored in the memory 1804. When executed, the computer executable instructions may cause the computer system 1801 to cause the sample analysis system 300 to perform one or more methods described herein. The results of the processing (e.g. Figure 2 The sensor diagram shown in FIG. 1800 may be displayed to a user via display adapter 1806 and display device 1808. User input for controlling the operation of computer system 1801 may be received from user input device 1812 via user input device adapter 1810.

[0237] Will understand, Fig.19 Some features of the computer system 1801 shown in FIG. 1804 may not exist in certain circumstances. For example, one or more of the plurality of computer devices 1801 may not require a display adapter 1806 or a display device 1808. This may be the case, for example, for certain computer devices 1801 that are used only for their processing capabilities and do not need to display information directly to a user. Similarly, a user input device adapter 1810 and a user input device 1812 may not be required. In its simplest form, the computer device 1801 includes a processor 1802 and a memory 1804.

[0238] As described above, the described method can be implemented using computer executable instructions. A computer program product or a computer readable medium may include or store computer executable instructions. A computer program product or a computer readable medium may include a hard drive, a flash memory, a read-only memory (ROM), a CD, a DVD, a cache, a random access memory (RAM), and / or any other storage medium in which information is stored for any duration (e.g., for an extended period of time, permanently, temporarily, for temporary buffering, and / or for a cache of information). A computer program may include computer executable instructions. A computer readable medium may be a tangible or non-temporary computer readable medium. The term "computer readable" includes "machine readable".

[0239] Although various specific combinations of components and method steps have been described, these are merely examples. Components and method steps may be combined in any suitable arrangement or combination. Components and method steps may also be omitted to leave any suitable combination of components or method steps.

[0240] The singular terms "a" and "an" should not be understood to mean "one and only one". Instead, unless otherwise specified, they should be understood to mean "at least one" or "one or more". The word "comprise" and its derivatives include "comprising", and "comprising" includes each of the stated features but does not exclude the inclusion of one or more other features.

[0241] The above implementations are described only by way of example, and the described implementations and examples are to be considered in all respects as illustrative and non-restrictive. It will be appreciated that the implementations described may be modified without departing from the scope of the present disclosure. It will also be appreciated that there are many modifications that are not described, but that fall within the scope of the appended claims.

[0242] Terms

[0243] Also disclosed in this article are the following terms:

[0244] 1. A method for delivering a plurality of sample solutions to a sensor surface for analysis, comprising:

[0245] a) introducing a first sample solution into a first channel, wherein the first channel is configured to deliver the sample solution to the sensor surface;

[0246] b) introducing a second sample solution into the first channel, wherein the second sample solution passes through a gas section in the first channel and is separated from the first sample solution;

[0247] c) allowing the first sample solution, the second sample solution and the gas segment to flow toward the sensor surface through the first channel;

[0248] d) extracting the gas segment from the first channel via the second channel before the gas segment reaches the sensor surface, so that the gas segment does not contact the sensor surface;

[0249] e) flowing the first sample solution and the second sample solution over the sensor surface; and

[0250] f) detecting the presence or absence of binding of an analyte from at least one of the sample solutions at the sensor surface.

[0251] 2. The method according to clause 1, wherein throughout steps a) - f), no running buffer solution is passed over the sensor surface.

[0252] 3. The method according to any preceding clause, wherein introducing the first and second sample solutions into the first channel comprises aspirating the first and second sample solutions from respective first and second sample solution reservoirs and injecting the sample solutions into the first channel.

[0253] 4. The method according to any preceding clause, wherein a first pump is configured to introduce a sample solution into the first channel and flow the sample solution through the first channel and over the sensor surface.

[0254] 5. The method according to any preceding clause, wherein before step a) and / or after step f), running buffer obtained from a running buffer reservoir is passed over the sensor surface by a second pump.

[0255] 6. A method according to any preceding clause, wherein the gas segment is extracted at most 40 seconds before the second sample solution reaches the sensor surface.

[0256] 7. A method according to any preceding clause, wherein the method is performed for three or more sample solutions, optionally wherein each sample solution is separated from any previous sample solution by a respective gas segment in the first channel.

[0257] 8. A method according to any preceding clause, wherein the sensor surface has a ligand immobilized thereto, and step f) comprises detecting the presence or absence of binding of an analyte from at least one sample solution to the ligand on the sensor surface.

[0258] 9. A method according to any preceding clause, wherein step f) comprises identifying whether an analyte in one of the sample solutions is bound to an analyte in another of the sample solutions, the analyte in the other sample solution having previously bound to the sensor surface.

[0259] 10. The method according to any preceding clause, wherein the first and second sample solutions are introduced into the first channel in a first order, and wherein the method further comprises:

[0260] The method steps are repeated with the first and second sample solutions introduced into the first channel in a second order different from the first order.

[0261] 11. The method according to any preceding clause, wherein the first sample solution comprises a first analyte and has a first pH value, and wherein the second sample solution has a second pH value and does not comprise an analyte.

[0262] 12. A method according to any preceding clause, wherein the first and second sample solutions have first and second respective concentrations, and wherein the method further comprises:

[0263] The concentration of at least one of the first and second sample solutions is modified, and the method steps are repeated using the modified solution(s).

[0264] 13. A method according to any preceding clause, wherein at least one sample solution comprises: a buffer; an antibody; an antigen; an enzyme; an agonist; an antagonist; a wash solution; or a sensor surface regeneration solution.

[0265] 14. A method according to any preceding clause, wherein the first sample solution contacts the sensor surface during a first time period, the second sample solution contacts the sensor surface during a second time period, and the delay between the end of the first time period and the beginning of the second time period is 40 seconds or less.

[0266] 15. The method according to any preceding clause, wherein the first sample solution comprises a membrane protein and the second sample solution comprises a lipid configured to at least partially cover the membrane protein.

[0267] 16. The method of any preceding clause, further comprising identifying complexes accumulated on the sensor surface, the complexes comprising analytes from at least two of the sample solutions.

[0268] 17. The method according to any preceding clause, further comprising identifying whether an analyte included in at least one of the sample solutions binds to the same or a different epitope as an analyte included in another of the sample solutions.

[0269] 18. A method according to any preceding clause, wherein step f) is based on evanescent wave sensing.

[0270] 19. The method according to any preceding clause, wherein step f) is based on surface plasmon resonance (SPR).

[0271] 20. A method according to any preceding clause, wherein the gas segment comprises air.

[0272] 21. A method according to any preceding clause, wherein the first and second channels form a generally T-shaped junction.

[0273] 22. A sample analysis system, comprising:

[0274] First channel;

[0275] Second channel; and

[0276] Sensor surface,

[0277] Wherein, the sample analysis system is configured to perform the following steps:

[0278] a) introducing a first sample solution into the first channel, the first channel being configured to deliver the sample solution to the sensor surface;

[0279] b) introducing a second sample solution into the first channel, wherein the second sample solution passes through a gas section in the first channel and is separated from the first sample solution;

[0280] c) allowing the first sample solution, the second sample solution and the gas segment to flow toward the sensor surface through the first channel;

[0281] d) extracting the gas segment from the first channel via the second channel before the gas segment reaches the sensor surface, so that the gas segment does not contact the sensor surface;

[0282] e) flowing the first sample solution and the second sample solution over the sensor surface; and

[0283] f) detecting the presence or absence of binding of an analyte from at least one of the sample solutions at the sensor surface.

[0284] 23. A computer configured to cause a sample analysis system to perform the method according to any one of clauses 1-21.

[0285] 24. A computer-readable storage medium comprising instructions which, when executed by a computer, cause the computer to cause a sample analysis system to perform the method according to any one of clauses 1-21.

Claims

1. A method for delivering a plurality of sample solutions to a sensor surface (102) for analysis, comprising: a) introducing (902) a first sample solution (502) into a first channel (506), the first channel being configured to deliver the sample solution to the sensor surface (102); b) introducing (904) a second sample solution (504) into the first channel; c) flowing (906) the first sample solution and the second sample solution (502, 504) through the first channel (506) and over the sensor surface (102); and d) detecting (912) at the sensor surface the presence or absence of binding of an analyte from at least one of the sample solutions (502, 504), Wherein, throughout steps a)-d), no running buffer solution is passed over the sensor surface (102).

2. The method according to claim 1, wherein: The second sample solution (502) passes through the gas section (503) in the first channel (506) and is separated from the first sample solution (504).

3. The method according to claim 2 further comprises, before the gas segment (503) reaches the sensor surface, extracting (908) the gas segment from the first channel (506) via a second channel (508) so that the gas segment (503) does not contact the sensor surface (102).

4. A method according to any preceding claim, wherein: Introducing the first and second sample solutions (502, 504) into the first channel (506) includes aspirating the first and second sample solutions from respective first and second sample solution reservoirs and injecting the sample solutions into the first channel.

5. A method according to any preceding claim, wherein: A first pump (404) is configured to introduce a sample solution into the first channel and flow the sample solution (502, 504) through the first channel (506) and over the sensor surface (102).

6. A method according to any preceding claim, wherein: Before step a) and / or after step d), running buffer obtained from a running buffer reservoir is passed over the sensor surface (102) by means of a second pump.

7. A method according to any preceding claim, wherein: The gas segment (103) is extracted at most 40 seconds before the second sample solution (504) reaches the sensor surface (102).

8. A method according to any preceding claim, wherein: The method is performed for three or more sample solutions, optionally wherein each sample solution is separated from any previous sample solution by a corresponding gas segment (103) in the first channel (506).

9. A method according to any preceding claim, wherein: The sensor surface (102) has a ligand immobilized thereon, and step d) comprises detecting the presence or absence of binding of an analyte from at least one sample solution (502, 504) to the ligand on the sensor surface (102).

10. A method according to any preceding claim, wherein: Step d) comprises identifying whether an analyte included in one of the sample solutions (502, 504) binds to an analyte included in another of the sample solutions, which has previously bound to the sensor surface (102).

11. A method according to any preceding claim, wherein: The first and second sample solutions (502, 504) are introduced into the first channel in a first order, and wherein the method further comprises: The method steps are repeated with the first and second sample solutions (502, 504) introduced into the first channel in a second order different from the first order.

12. A method according to any preceding claim, wherein: The first sample solution (502) includes a first analyte and has a first pH value, and wherein the second sample solution (504) has a second pH value and does not include an analyte.

13. A method according to any preceding claim, wherein: The first and second sample solutions (502, 504) have first and second respective concentrations, and wherein the method further comprises: The concentration of at least one of the first and second sample solutions (502, 504) is modified, and the method steps are repeated using the modified solution.

14. A method according to any preceding claim, wherein: At least one sample solution (502, 504) includes: a buffer; an antibody; an antigen; an enzyme; an agonist; an antagonist; a wash solution; or a sensor surface regeneration solution.

15. A method according to any preceding claim, wherein: The first sample solution (502) contacts the sensor surface (102) during a first time period, the second sample solution (504) contacts the sensor surface (102) during a second time period, and a delay between the end of the first time period and the beginning of the second time period is 40 seconds or less.

16. A method according to any preceding claim, wherein: The first sample solution (502) includes a membrane protein, and the second sample solution includes a lipid configured to at least partially cover the membrane protein.

17. The method of any preceding claim, further comprising identifying complexes accumulated on the sensor surface (102), the complexes comprising analytes from at least two of the sample solutions (502, 504).

18. The method according to any preceding claim, further comprising identifying whether an analyte included in at least one sample solution (502, 504) binds to the same or a different epitope as an analyte included in another of the sample solutions.

19. A method according to any preceding claim, wherein: Step d) is based on evanescent wave sensing.

20. A method according to any preceding claim, wherein: Step d) is based on surface plasmon resonance (SPR).

21. A method according to any preceding claim, wherein: The gas section (103) includes air.

22. A method according to any preceding claim, wherein: The first and second passages (506, 508) form a generally T-shaped junction.

23. A sample analysis system, comprising: First channel (506); as well as a sensor surface (102), Wherein, the sample analysis system is configured to perform the following steps: a) introducing a first sample solution (502) into the first channel (506), wherein the first channel (506) is configured to deliver the sample solution to the sensor surface (102); b) introducing a second sample solution (504) into the first channel (506); c) flowing the first sample solution (502) and the second sample solution (504) through the first channel (506) and over the sensor surface (102); and d) detecting the presence or absence of binding of an analyte from at least one of the sample solutions (502, 504) at the sensor surface (102), Therein, throughout steps a)-d), no running buffer solution is passed over the sensor surface.

24. A method for testing multiple groups of sample solutions, comprising: providing (1402) a first set of sample solutions, wherein the first set of sample solutions includes at least three sample solutions; obtaining a first binding signal (1406) by performing an assay (1404) using the first set of sample solutions, during which each sample solution in the first set of sample solutions is sequentially flowed over a sensor surface; providing a second set of sample solutions (1408), wherein the second set of sample solutions includes a subset of the first set of sample solutions and a buffer sample solution; obtaining a second binding signal (1412) by performing an assay (1410) using the second set of sample solutions, during which each sample solution in the second set of sample solutions is sequentially flowed over the sensor surface; and A third combined signal (1416) is generated by subtracting (1414) the second combined signal from the first combined signal.

25. The method according to claim 24, wherein: Providing the first and / or second set of sample solutions includes introducing the respective sample solutions into a channel configured to deliver the sample solutions to the sensor surface.

26. The method according to claim 25, wherein: Each sample solution introduced into the channel is separated from any previous sample solution by passing through a corresponding gas segment in the channel.

27. The method of claim 26, further comprising extracting each gas segment from the channel via another channel before the respective gas segment reaches the sensor surface such that each respective gas segment does not contact the sensor surface.

28. The method according to any one of claims 25 to 27, wherein: Introducing the first and / or second set of sample solutions includes aspirating the corresponding sample solutions from corresponding sample solution reservoirs and injecting the sample solutions into the channel.

29. The method according to any one of claims 24 to 28, wherein: Obtaining the first and / or second binding signal comprises detecting the presence or absence of binding involving an analyte from the respective sample solution at the sensor surface.

30. The method of claim 29, wherein: The sensor surface has a ligand immobilized thereto, and obtaining the first and / or second binding signal comprises detecting the presence or absence of binding of an analyte from at least one sample solution to the ligand on the sensor surface.

31. The method according to claim 29 or 30, wherein: Obtaining the first and / or second binding signal comprises identifying whether an analyte included in one of the sample solutions binds to an analyte included in another of the sample solutions, the analyte in the other sample solution having previously bound to the sensor surface.

32. The method according to any one of claims 24 to 31, wherein: The first group of sample solutions includes a first sample solution and a second sample solution, wherein the first sample solution generates a dissociation signal equal to or greater than an association signal generated by the second sample solution when the second sample solution reaches the sensor surface, and wherein the second group of sample solutions does not include the second sample solution.

33. A method according to any one of claims 24 to 32, wherein: The first set of sample solutions includes a first sample solution and a second sample solution, wherein an analyte in the second sample solution can bind to an analyte in the first sample solution and a ligand on the sensor surface, and wherein the second set of sample solutions does not include the first sample solution.

34. The method according to any one of claims 24 to 33, wherein: The first set of sample solutions includes a first antibody, an antigen and a second antibody.

35. The method of claim 34, wherein: The second set of sample solutions does not include the antigen.

36. The method according to claim 34 or 35, wherein: The second set of sample solutions does not include the second antibody.

37. The method of any one of claims 24 to 36, further comprising determining whether binding of an analyte in a second sample solution in the first set of sample solutions is dependent on the presence of an analyte from a first sample solution in the first set of sample solutions based on the third binding signal.

38. The method of any one of claims 24 to 37, further comprising determining whether an analyte in a first sample solution in the first set of sample solutions binds to the same epitope as an analyte in a second sample solution in the first set of sample solutions based on the third binding signal.

39. The method according to any one of claims 24 to 38, wherein: At least one sample solution includes: a buffer; an antibody; an antigen; an enzyme; an agonist; an antagonist; a wash solution; or a sensor surface regeneration solution.

40. The method according to any one of claims 24 to 39, wherein: Performing an assay using the first and / or second set of sample solutions is based on evanescent wave sensing.

41. The method according to any one of claims 24 to 40, wherein: The assay performed using the first and / or second set of sample solutions is based on surface plasmon resonance (SPR).

42. A sample analysis system comprising: A sensor (102) having a surface over which a sample solution (502, 504) can flow; as well as at least one channel (506, 508), the at least one channel (506, 508) configured to deliver a sample solution to the sensor surface; Wherein, the sample analysis system is configured as follows: providing a first set of sample solutions to the at least one channel, wherein the first set of sample solutions includes at least three sample solutions; performing an assay in which each sample solution in the first set of sample solutions is sequentially flowed over the sensor surface (102) to obtain a first binding signal; providing a second set of sample solutions to the at least one channel, wherein the second set of sample solutions includes a subset of the first set of sample solutions and a buffer sample solution; performing an assay in which each sample solution in the second set of sample solutions is sequentially flowed over the sensor surface (102) to obtain a second binding signal; and A third combined signal is generated by subtracting the second combined signal from the first combined signal.

43. A computer (600) configured to cause a sample analysis system to perform the method according to any one of claims 1-22 or 24 to 41.

44. A computer-readable storage medium comprising instructions which, when executed by a computer, cause the computer to cause a sample analysis system to perform the method of any one of claims 1-22 or 24 to 41.

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