Multi-specimen circular dichroism measuring device
Patent Information
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- Filing Date
- 2026-01-06
- Publication Date
- 2026-08-13
Smart Images
Figure JP2026000127_13082026_PF_FP_ABST
Abstract
Description
Multi-sample circular dichroism measurement device Related application
[0001] This application claims the priority of Japanese Patent Application No. 2025-017203 filed on February 5, 2025, which is incorporated herein by reference.
[0002] The present invention relates to a device for measuring circular dichroism spectra for a large number of samples.
[0003] In recent years, due to the increasing interest in antibody pharmaceuticals, there has been a growing need to measure multiple samples using a circular dichroism (CD) measurement device capable of evaluating the higher-order structure (secondary and tertiary structures) of proteins. Higher-order structure (HOS) evaluation is essential in the development of follow-up products (biosimilars) of antibody pharmaceuticals. For example, it is used for the identity evaluation of a pioneer product (innovator) and a follow-up product (see, for example, Patent Document 1). In addition to the development of biosimilars, HOS evaluation is also performed in stability evaluations to assess whether a sample denatures or inactivates due to changes in temperature, salt concentration, and pH. At this time, a large number of samples with slightly different conditions are measured for statistical comparative studies.
[0004] For spectral measurement of multiple samples, an autosampler is usually used (see, for example, Patent Document 2). In a system combining a spectrophotometer, an autosampler, and a flow cell, automatic measurement of multiple samples is possible by automatically performing a series of operations including transporting the sample to the flow cell (suction by a pump), discharging the sample from the flow cell after measurement is completed (discharge by a pump), and cleaning the flow cell and the flow path.
[0005] When performing CD measurement on multiple samples using a single-beam measurement device, the measurement order of the samples, that is, the sequence setting, is important to reduce the influence of drift (time change) of the measurement device. When there are multiple types of samples, such as in stability evaluation, and there are N samples for each type of sample, instead of measuring the N samples of the first type of sample and then repeating the measurement of the N samples of the next type of sample, it is recommended to measure one sample of each type of sample in sequence for all types of samples and repeat this N times.
[0006] Japanese Patent Publication No. 2022-080555 Japanese Patent Publication No. 2007-187474
[0007] However, the first problem with conventional CD measuring devices is that when dealing with multiple types of samples, or when the sample size (N) for a single type of sample is large, the user's burden in setting up the sequence increases. This is because the user had to set the measurement order for each sample individually.
[0008] Furthermore, when using samples such as proteins dissolved in a solvent, it is necessary to measure only the solvent (buffer) immediately before or after measuring the sample for baseline correction. For example, when measuring three types of samples A, B, and C with N=3, and the buffers are denoted as Ra, Rb, and Rc, the user needs to set up a complex sequence combining the samples and buffers, such as Ra→A1→Rb→B1→Rc→C1→Ra→A2→Rb→B2→Rc→C2→Ra→A3→Rb→B3→Rc→C3.
[0009] Furthermore, conventional CD measuring devices perform the necessary data processing and spectral analysis on each individual spectral data point. However, in the case of sequence measurements combining several types of samples and their respective buffers, as described above, a second problem arises: the user must read out the desired data point from a large number of spectral data points stored in a computer's memory device, and then perform the appropriate data processing and spectral analysis on each individual data point, which is extremely time-consuming. There is also the possibility of errors such as reading the wrong data. For example, when subtracting spectra during baseline correction, there is a possibility of making mistakes in the combination of spectra or the order in which they are subtracted, or when evaluating identity, there is a possibility of misidentifying the spectrum to be evaluated.
[0010] The present invention aims to automate sequence setting in multi-sample CD measurement, and to automate data processing or spectral analysis of a large amount of spectral data obtained in multi-sample CD measurement.
[0011] In other words, the multi-sample circular dichroism (CD) measuring device of the present invention is a multi-sample circular dichroism (CD) measuring device for measuring the circular dichroism (CD) spectra of multiple samples, comprising: a flow cell; an autosampler for transporting the samples to the flow cell in order of measurement and for discharging them from the flow cell; a measuring instrument unit for measuring the CD spectra of the samples in the flow cell; and a computer for controlling the autosampler and the measuring instrument unit and for processing the CD spectra from the measuring instrument unit, wherein the computer includes a sequence setting function for determining the measurement order of the samples, and the sequence setting function accepts the following input information (1) to (3): (1) information about the sample (e.g., sample name, identification number, concentration, etc.), (2) information about the solvent contained in the sample, and (3) information about the number of samples (N: N is a natural number of 1 or more), The system acquires attribute information (R, S1, S2, ...) that distinguishes whether the sample and the solvent relate to a standard sample (R) or to any of the samples to be evaluated (S1, S2, ...), and type information (S, B) that distinguishes the sample and the solvent, and uses the following rules (4) to (6): (4) For each attribute (R, S1, S2, ...), one sample (S) and one solvent (B) are arranged as one set, with one solvent (B) sample placed immediately before or after one sample (S); (5) The sets of sample (S) and solvent (B) samples for all attributes (R, S1, S2, ...) are arranged in a single row; and (6) The arrangement of the sample sets is repeated as many times as there are samples (N) of the sample, thereby determining the measurement order of the samples.
[0012] With this configuration of a multi-sample circular dichroism analyzer, the first problem is addressed by inputting "sample information, information on the solvent contained in the sample, and information on the number of samples (N)," which automatically sets the recommended sequence.
[0013] Furthermore, the sequence setting function preferably functions to determine the positions in the autosampler where the samples are arranged in a vertical and horizontal plane, by using the attribute information (R, S1, S2, ...) and the type information (S, B) to determine the positions in the autosampler where the samples are arranged vertically and horizontally, according to the following rules (7) and (8): (7) The rows of sample sets according to rule (5) are arranged vertically, and (8) Samples for which both the attribute information and the type information are the same are arranged horizontally.
[0014] With the multi-sample circular dichroism analyzer configured as described above, the appropriate arrangement of samples in the autosampler is automatically determined.
[0015] Furthermore, it is preferable that the computer includes a storage unit capable of storing the CD spectral data with attribute information (R, S1, S2, ...) and type information (S, B) attached to or associated with the CD spectral data, and that when executing a predetermined data processing, the computer is configured to read the CD spectral data to be processed from the storage unit using the attribute information (R, S1, S2, ...) and type information (S, B).
[0016] Here, the data processing preferably includes at least one of the following: baseline correction, calculation between spectral data, peak detection, waveform separation, and spectral analysis. Furthermore, it is preferable that the spectral analysis is for evaluating the identity of a protein or evaluating its higher-order structure.
[0017] With the multi-sample circular dichroism analyzer configured as described above, the second problem can be addressed by the fact that when performing various data processing (including spectral analysis) on a large number of CD spectral data, the computer can read the CD spectral data to be processed from the storage unit using attribute information (R, S1, S2, ...) and type information (S, B), thus enabling the automation of these data processing operations.
[0018] This is an overall configuration diagram of a multi-sample CD measuring device according to the present invention. This is a diagram showing an example of the configuration of the autosampler of the multi-sample CD measuring device. This is an explanatory diagram of the search function of the multi-sample CD measuring device. This is a measurement flow diagram of the multi-sample CD measuring device. This is an example of the monitor screen (input screen) of the multi-sample CD measuring device. This is an example of the monitor screen (sample arrangement diagram) of the multi-sample CD measuring device. This is an example of the monitor screen (measurement order list) of the multi-sample CD measuring device. This is an example of the monitor screen (at the start of measurement) of the multi-sample CD measuring device. This is an example of the monitor screen (during measurement) of the multi-sample CD measuring device. This is an example of the monitor screen (evaluation results) of the multi-sample CD measuring device.
[0019] Hereinafter, an embodiment of the multi-sample circular dichroism (CD) measuring device according to the present invention will be described based on the drawings. Figure 1 is a schematic overall configuration diagram of the multi-sample CD measuring device 10 of this embodiment. The multi-sample CD measuring device 10 comprises a CD measuring instrument unit 14 in which a flow cell holder 12 (with a water-cooled Peltier type temperature control function) is installed in the sample chamber, an autosampler 22 having a nozzle 20 connected to the lower inlet / outlet of the flow cell 16 via a first flow path 18, a drying unit 26 connected to the upper inlet / outlet of the flow cell 16 via a second flow path 24, and a syringe pump 30 connected to the drying unit 26 via a third flow path 28. The drying unit 26 has a three-way valve 32 and a drying pump 34, and the second flow path 24, the third flow path 28 and the drying pump 34 are connected to the three-way valve 32.
[0020] Figure 2 shows the vial holder 40, washing solution bottle 42, nozzle wipe 44, and drainage bottle 46 installed in the autosampler 22. The nozzle 20 can be moved in a predetermined order to the desired vials 40A, 40B, ... on the vial holder 40, the washing solution bottle 42, the nozzle wipe 44, and the drainage bottle 46 by the nozzle moving device of the autosampler 22.
[0021] Using Figure 1, we will explain the process of transporting the sample from the vial to the flow cell 16. As an example, we will explain a series of operations including "washing," "drying," "sample transport," "measurement," "sample discharge," and "drying."
[0022] First, during cleaning, the three-way valve 32 opens the second flow path 24 and the third flow path 28. The nozzle 20 is then inserted into the cleaning solution bottle 42. When the syringe pump 30 is operated in suction mode, a predetermined volume of cleaning solution is transported from the nozzle 20 to the pump. This cleaning solution reaches the flow cell 16, cleaning the first flow path 18 and the flow cell 16.
[0023] Next, move the nozzle 20 to the drainage bottle 46 (or the drainage port leading to the drainage bottle 46). When the syringe pump 30 is operated in discharge mode, the cleaning solution is pushed towards the nozzle 20, and the cleaning solution that returns to the nozzle 20 is discharged into the drainage bottle 46. Once discharge is complete, stop the syringe pump 30.
[0024] During drying, the solenoid valve of the three-way valve 32 is switched to open the drying pump 34 and the second flow path 24. The nozzle 20 can remain in the position of the drainage bottle 46. By running the drying pump 34 for a predetermined time, air (or nitrogen gas) from the drying pump 34 is sent into the second flow path 24, so that the inside of the second flow path 24, the flow cell 16 and the first flow path 18 are dried. The above is an example of one cycle of operation when cleaning the flow cell 16.
[0025] When using multiple types of cleaning solutions, repeat the above cleaning and drying process for each type of cleaning solution. Note that when moving the nozzle 20, there is a step to remove residue from the nozzle tip with the nozzle wipe 44, but this will not be explained here.
[0026] After washing the nozzle 20, the first flow path 18, and the flow cell 16 a predetermined number of times, the nozzle 20 is moved to a desired vial (e.g., 40A). By inserting the nozzle 20 into vial 40A and aspirating the sample, the sample is transported to the flow cell 16 (resulting in the state shown in Figure 1).
[0027] In this embodiment, the timing of a sample's arrival in the flow cell 16 can be detected by monitoring the adjustment voltage (HT voltage) applied to the detector 36 that detects transmitted light from the flow cell 16 (search function). The HT voltage, which is the monitored signal here, is a voltage used to adjust the gain of the detector 36 so that the amount of light received by the detector 36 remains constant. When the HT voltage is monitored during sample transport, the HT voltage remains relatively high until the sample arrives in the flow cell 16 (there is air inside the flow cell 16), and then decreases when the sample arrives in the flow cell 16. This is because the presence of the sample inside the flow cell 16 increases the amount of light transmitted through the flow cell 16. When performing this search function, it is advisable to set the wavelength of the light transmitted through the flow cell 16 to a wavelength band outside the absorbance band of the sample in order to avoid the influence of the sample's absorbance.
[0028] By using the search function described above, it is possible to stop the syringe pump 30 when the sample reaches the flow cell 16 without having to accurately determine in advance the amount of gas that the nozzle 20 should aspirate after aspirating the sample, that is, the air volume required to transport the sample to the flow cell 16 (air volume for delivery). This ensures that the CD measurement is performed with the sample reliably present in the flow cell 16. Therefore, even when measuring samples with different viscosities, there is no need to readjust the air volume. Even when samples with multiple viscosities are included, there is no need to readjust the air volume each time the viscosity of the sample changes, saving time and effort. When automatically measuring multiple samples consisting of samples of various viscosities in a single sequence, the search function may be executed for each sample, or the air volume may be set for each group of samples, such as setting a certain air volume for a certain range of samples. Alternatively, a delivery test using the search function may be performed before the actual measurement to determine the air volume for delivery (see Figure 3). As shown in Figure 3, the monitor signal (HT voltage) during the delivery test may be displayed graphically in real time. In this example, the HT voltage decreases when the air volume (horizontal axis) drawn in by the syringe pump 30 reaches 1140 μL, so this air volume is set as the air volume for fluid delivery.
[0029] Furthermore, by saving the HT voltage monitor signal along with the measurement data, the monitor signal can be used to investigate the cause of problems. For example, if there is a problem where measurement was not performed, the monitor signal can be used to determine whether the cause was that there was no sample in the flow cell, or due to some other equipment malfunction, or which sample number is faulty.
[0030] After the measurement is complete, the sample is discharged and dried as follows: For sample discharge, the nozzle 20 is moved to the drain bottle 46 (or the drain port leading to the drain bottle 46). When the syringe pump 30 is operated in discharge mode, the sample in the flow cell is pushed towards the nozzle, and the sample that returns to the nozzle 20 is discharged into the drain bottle 46. Once discharge is complete, the syringe pump 30 is stopped.
[0031] During drying after measurement, the three-way valve 32 opens the drying pump 34 and the second flow path 24, similar to the drying before measurement. The nozzle 20 can remain in the position of the drainage bottle 46. By operating the drying pump 34 for a predetermined time, air (or nitrogen gas) from the drying pump 34 is sent into the second flow path 24, so that the inside of the second flow path 24, the flow cell 16, and the first flow path 18 are dried. The above steps, from washing to sample discharge and drying, represent one cycle of operation when measuring one sample in a flow cell.
[0032] Figure 4 shows the overall operation flow of the multi-sample CD measurement device. This operation flow is the operation flow of the CD measurement program, which is executed by a computer connected to the CD measurement equipment unit 14 (capable of simultaneously measuring CD spectra and fluorescence spectra), autosampler 22, drying unit 26, and syringe pump 30. When the program is executed, the computer displays confirmation input screens for each step on a display device or the like, so that the user can proceed with the measurement while confirming (and inputting information as needed) according to the procedure.
[0033] In step 1, the user selects whether to perform spectrum acquisition or identity verification testing. This section describes the operation flow of identity verification testing, which allows the identity of the sample under evaluation and the standard sample to be evaluated based on their respective spectral data. Identity can be evaluated using either CD spectra or fluorescence spectra.
[0034] In the system setup in step 2, the system automatically recognizes the detectors connected to the CD measuring instrument unit 14, and displays a list of available detectors (name, serial number, etc.) along with information on previously connected detectors. The user can easily select the detector to use on the screen. Similarly, connected accessories (cell units, external accessories, etc.) are also automatically recognized and displayed in a list. The names and serial numbers of the detectors and accessories used for measurement are added to the measurement data.
[0035] In step 3, setting the conditions, you can choose to open an existing conditions file or create a new one. If you open an existing conditions file, proceed to step 9, the liquid delivery test. If you create a new one, name the conditions file and set the save location. Since the measurement data for both CD spectra and fluorescence spectra will be saved together in this location, set the file names for the spectral data to be saved. The spectral files to be saved include raw (unprocessed) spectral files, integrated spectral files, baseline-corrected spectral files, data-processed spectral files, reference model files, and identity verification test result files. For raw spectral files, set it so that the raw spectral file for baseline correction (i.e., the solvent) and the raw spectral data of the sample itself are saved separately.
[0036] Note that only the final spectrum file (the spectrum file after data processing) with all data processing, such as integration and baseline correction, completed should remain. Intermediate files, such as the raw spectrum file, can be deleted once data processing is complete. Next, proceed to setting the conditions in steps 4-8.
[0037] In step 4, mode selection, choose the measurement mode according to the type of sample. The sample type here refers to, for example, proteins and nucleic acids. Measurement modes include, for example, protein (secondary structure), protein (tertiary structure), nucleic acid, and advanced mode. Depending on the measurement mode, appropriate measurement parameters (measurement wavelength, data interval, response, etc.) for the sample are automatically set. When measuring samples other than proteins and nucleic acids, or when measuring fluorescence (fluorescent labeling, etc.) that is not derived from the sample, even if it is a protein or nucleic acid, select the advanced mode (where all settings can be arbitrarily selected).
[0038] In step 5, setting up the identity verification test, you will define the conditions for the identity verification test. When evaluating the identity between the standard sample and the sample to be evaluated, you will choose whether to use the spectrum of one sample to be evaluated or the spectra of multiple samples to be evaluated. You will also set the significance level and other parameters. Furthermore, you will set the calculation of spectral distance, including the method for correcting concentration errors and the type of weighting used.
[0039] In step 6, the sequence setting determines the positions (multiple sample arrangement diagram) for placing the samples in the autosampler 22 based on the sample information. The computer first obtains the following input information (1) to (3): (1) sample information (e.g., sample name, identification number, concentration, etc.), (2) information on the solvent contained in the sample, and (3) information on the number of samples (N: N is a natural number greater than or equal to 1), and determines the measurement order for all samples. Next, the computer determines the positions for placing the samples in the autosampler 22 in a vertical and horizontal plane.
[0040] The computer uses attribute information (R, S1, S2, ...) and type information (S, B) to determine the measurement order. Attribute information distinguishes whether the sample and solvent relate to the standard sample (R) or to one of the samples to be evaluated (S1, S2, ...), while type information distinguishes between the sample (S) and the solvent (B). Attribute information (R, S1, S2, ...) and type information (S, B) are assigned to input information (1) and input information (2) respectively by the user on the input screen. Figure 5 shows an example of the input screen.
[0041] In the upper part of Figure 5, there is an input field for the number of groups. The number of groups indicates how many types of samples are being evaluated, and here we will explain using a group number of 3. This group number indicates, for example, how many types of biosimilars there are for an original antibody drug (innovator), or how many types of samples have been modified by adding changes such as temperature, salt concentration, and pH to a standard sample (e.g., native). The group number is different from the number of samples (N). Both the standard sample and the samples being evaluated are in a mixed state of the substance of the sample itself and some kind of solvent (buffer). Based on the group number, input fields for the standard sample and the samples being evaluated are formed. In the first column of the input field, the attribute information field displays "R" to indicate the standard sample and "S1 to S3" to indicate the first to third sample groups. In the second column, the type information field, the sample (S) and solvent (B) fields are formed in two rows for each attribute (R, S1 to S3). From the third column onward, input fields are formed for entering information about the samples (samples or solvents) that are distinguished by the attribute information and type information. Information about the specimen (sample or solvent) includes, for example, the name of the specimen, identification number, concentration, unit of concentration, and the name of the specimen (or solvent).
[0042] Therefore, the first row of the input field contains information about the solvent of the standard sample, distinguished by attribute R and type B; the second row contains information about the standard sample, distinguished by attribute R and type S; the third row contains information about the solvent of the first sample group, distinguished by attribute S1 and type B; and the fourth row contains information about the sample of the first sample group, distinguished by attribute S1 and type S. Similarly, information about the solvent and sample for each sample group is entered sequentially in the subsequent rows.
[0043] In Figure 5, the "Reference (or Sample Group) Baseline" in the "Sample Name" column means that the sample consists only of the solvent (buffer). This is because the spectral data of the solvent is necessary when baseline-correcting the spectra of the standard sample or the sample being evaluated.
[0044] The upper limit of the number of groups may be set so that the numerical value represented by "((the number of groups) + 1) × 2" does not exceed the number of specimens (for example, the number of wells in one row) that can be arranged in a row using one or more multi-specimen trays (such as the vial holder 40 in FIG. 2) installed in the autosampler 22.
[0045] Next, the determination of the measurement order of specimens by the computer will be described using FIG. 7. The computer follows the following rules (4) to (6): (4) For each attribute (R, S1, S2,...), one specimen of the sample (S) and one specimen of the solvent (B) are set as a set, and one specimen of the solvent (B) is arranged immediately before or after one specimen of the sample (S). (5) Arrange the sets of specimens of the sample (S) and the solvent (B) for all attributes (R, S1, S2,...) in a row. And (6) Repeat the arrangement of the sets of specimens by the number of specimens (N) of the sample to determine the measurement order of all specimens.
[0046] In the display image of FIG. 7, the measurement order of all specimens determined with the number of specimens in each sample group being N = 10 is listed. The first column of the list is a column for displaying attribute information by color, and the second column is a column for the position information of the specimens to be placed in the autosampler 22.
[0047] The specimens in the first and second rows of the list belong to attribute R, and the column is, for example, "pink". The specimen of solvent B is in the first row, and the specimen of sample S is in the second row. In the attribute column, considering visibility, instead of the original attribute R (standard sample), B (solvent) indicating its type information is displayed in the first row, and the original attribute R (standard sample) is displayed in the second row. The specimens in the third and fourth rows of the list belong to attribute S1, and the column is, for example, "orange". The specimen of solvent B is in the third row, and the specimen of sample S is in the fourth row. In the attribute column, considering visibility, instead of the original attribute S1 (first sample group), B (solvent) indicating its type information is displayed in the first row, and the original attribute S1 (first sample group) is displayed in the second row. The specimens in the fifth and sixth rows of the list belong to attribute S2, and the column is, for example, "green". The specimen of solvent B is in the fifth row, and the specimen of sample S is in the sixth row. In the attribute column, considering visibility, instead of the original attribute S2 (second sample group), B (solvent) indicating its type information is displayed in the first row, and the original attribute S2 (second sample group) is displayed in the second row. The specimens in the seventh and eighth rows of the list belong to attribute S3, and the column is, for example, "blue". The specimen of solvent B is in the seventh row, and the specimen of sample S is in the eighth row. In the attribute column, considering visibility, instead of the original attribute S3 (third sample group), B (solvent) indicating its type information is displayed in the first row, and the original attribute S3 (third sample group) is displayed in the second row.
[0048] In this way, from the first row to the eighth row, the first set of specimens (solvent B and sample S) of each attribute (R, S1, S2,...), that is, 8 specimens are arranged. From the ninth row to the sixteenth row, in the same way as from the first row to the eighth row, 8 specimens which are the second set of specimens of each attribute are arranged. Such an arrangement is repeated after the seventeenth row, and finally, 8 specimens which are the tenth set of specimens of each attribute are arranged.
[0049] In this way, based on the information of the samples and solvents in the input column, the computer uses the attribute information (R, S1, S2,...) and the type information (S, B) to arrange a total of 80 specimens (= (3 + 1) × 2 × 10) according to a predetermined rule so that the number of specimens in each sample group is N = 10, and determines the measurement order of all specimens.
[0050] Next, we will explain how the computer determines the arrangement of all samples on the autosampler 22, using Figure 6. The computer determines the position of all samples on the autosampler 22 using the measurement order determined above, according to the following rules (7) and (8): (7) The rows of sample sets according to rule (5) are arranged vertically, and (8) Samples with the same attribute information and type information are arranged horizontally. Here, we will explain the case where the multi-sample plate of the autosampler 22 is a microplate that can arrange a total of 96 samples in 8 rows and 12 columns. The vertical position of the microplate is represented by A to H, and the horizontal position is represented by 1 to 12. For example, the position information of the 2nd row, 3rd column is shown as "B3".
[0051] The image in Figure 6 displays the positions of the samples determined by rules (7) and (8) above in a planar layout. The second column of the list in Figure 7 also displays the information of the determined positions. Specifically, the first eight samples (1st to 8th) are placed in the first column of the microplate, the ninth to sixteenth samples (8) are placed in the second column, and similarly, the seventeenth to twenty-fourth samples (8) are placed in the third column. This arrangement is repeated for the fourth column and beyond, with the 73rd to 80th (last) samples placed in the tenth column. This automatic setup of the sample layout significantly reduces the user's sequence setting burden. The determined layout is designed to minimize the effects of measurement device drift and to allow for the shortest possible measurement time. Furthermore, by displaying the sample information on the layout diagram (the position of a single well) when the mouse cursor is hovered over it, the user can more easily confirm the sample information.
[0052] Returning to the operation flow in Figure 4, in step 7, the measurement and data processing settings, the measurement conditions for the CD spectrum and fluorescence spectrum (such as the number of integrations), and whether to turn the temperature control ON or OFF are set. Also, the data processing to be applied is set. For example, various types of data processing (e.g., smoothing, FFT filtering, peak detection, waveform separation) may be displayed in a list for the user to select. Essential data processing such as integration and baseline correction does not need to be displayed in the list.
[0053] In step 8, the settings for the autosampler are configured, including the conditions for the autosampler 22 (sample volume, sample aspiration rate, washing solution, drying time, etc.).
[0054] In the liquid delivery test in step 9, the sample (or washing solution) is actually transported to the flow cell 16 according to the conditions set in step 8, and the timing of arrival is detected using the search function to determine the volume of air used for liquid delivery during measurement.
[0055] In step 10, the measurement of multiple samples is performed using the autosampler 22. Figure 8 shows the display screen at the start of the measurement. The display screen shows the arrangement of samples for each plate, the position of the washing solution, and the position of the nozzle wipe (NW). The user sets all samples on the plates based on the arrangement diagram. Here, the arrangement diagram uses only plate 1, but if there are many sample groups, the arrangement diagram determined using both plates 1 and 2 will be displayed. The user also sets the washing solution (for example, three types: commercially available alkaline detergent for cells, ultrapure water, and ethanol) and nozzle wipe (NW) according to the display screen. When the user presses the measurement start button, the multi-sample measurement begins.
[0056] Figure 9 shows an example of the display screen during measurement, with a diagram of the sample arrangement on the left and a graph of the spectrum being measured on the far right. For example, as shown in Figure 9, the sample being measured and the sample that has been measured can be displayed in different colors to make it easier for the user to understand the progress of multi-sample measurement. In this example, it can be seen that the sample at position "A5" on plate 1 is being measured.
[0057] In this embodiment, the CD measuring instrument unit simultaneously measures both the CD spectrum and the fluorescence spectrum of a sample in the flow cell. Therefore, the computer processes the CD spectrum data and the fluorescence spectrum data separately. The computer also acquires data on the HT voltage value for each scanning wavelength applied to the detector for the CD spectrum. The CD measuring instrument unit performs spectrum measurements a set number of times for each sample transported to the flow cell. The computer performs multiple data processing operations, such as "integration," "baseline correction," and "smoothing," on the raw spectrum data from the CD measuring instrument unit.
[0058] Returning to the operation flow in Figure 4, in step 11, the raw spectral data acquired for each sample is integrated. In step 12, baseline correction is performed on the integrated spectral data. In step 13, other data processing (if smoothing is selected) is performed on the baseline-corrected spectral data. The process is not limited to smoothing; other configured data processing (e.g., optical constant calculation) may also be performed.
[0059] Steps 11-13, which involve data processing, are performed for each spectral data set from a single sample, and therefore will be repeated for each sample. If you wish to further analyze the spectral data obtained through this data processing, you may transfer this data to another analysis program.
[0060] In step 14, the creation of the reference model, the reference model is created based on the processed standard sample spectral data once the data processing of the standard sample spectral data is complete.
[0061] In the identity verification test in step 15, the spectral distances of the reference model and the sample under evaluation are calculated under conditions set based on the spectral data of the reference model and the sample under evaluation, and the identity between the standard sample and the sample under evaluation is statistically evaluated.
[0062] In this embodiment, the computer stores the measured spectral data (raw spectral data) and the spectral data obtained through each data processing and analysis, assigning or associating attribute information (R, S1, S2, ...) and type information (S, B) to these spectral data. When executing a pre-specified data processing, the computer can smoothly read the spectral data to be processed from the storage unit using the attribute information (R, S1, S2, ...) and type information (S, B). Therefore, even when measuring a large amount of spectral data from multiple samples, it becomes possible to automate pre-specified data processing and analysis.
[0063] In the results display in step 16 (for example, Figure 10), the results of the identity verification test for each sample being evaluated are displayed. For example, if you want to analyze the higher-order structure (HOS) of a protein in more detail, you can transfer the spectral data obtained from the data processing and identity verification test up to this point to another analysis program.
[0064] If a search error occurs during the transport of a sample to the flow cell 16, the measurement data will be saved with error information, and multi-sample measurement will continue. The sample with the search error may be clearly indicated in the results display column of Figure 10. Alternatively, the sample data with the search error may not be used for data processing such as integration.
[0065] The data measured by the multi-sample CD measuring device 10 of this embodiment may include CD spectra, fluorescence spectra, HT spectra, absorbance spectra calculated from HT, etc., and these are displayed as multi-channel data. By acquiring spectral data from multiple samples using the sequence setting method of this embodiment, it is possible to precisely set what kind of data processing to perform on each channel of the spectrum, and furthermore, the conditions for data processing and analysis can be easily set all at once for the vast amount of spectral data from multiple samples, and such data processing and analysis can be executed smoothly.
[0066] In this embodiment, a CD measuring instrument capable of simultaneously measuring CD spectra and fluorescence spectra was used. However, the instrument may also be configured to enable ultraviolet-visible spectroscopy (UV-vis) measurement, or it may be configured as a multi-sample optical measuring device capable of measuring one or more optical spectral data from CD spectra, fluorescence spectra, and UV-vis spectra.
[0067] 10 Multi-sample circular dichroism (CD) analyzer 12 Flow cell holder 14 CD measuring instrument section 16 Flow cell 18 First channel 20 Nozzle 22 Autosampler 24 Second channel 26 Drying unit 28 Third channel 30 Syringe pump 32 Three-way valve 34 Drying pump 36 Detector 40 Vial holder 42 Washing solution bottle 44 Nozzle wipe 46 Drainage bottle
Claims
1. A multi-sample circular dichroism (CD) analyzer for measuring the circular dichroism (CD) spectra of multiple samples, comprising: a flow cell; an autosampler for transporting the samples to the flow cell in order of measurement and for discharging them from the flow cell; a measuring instrument unit for measuring the CD spectra of the samples in the flow cell; and a computer for controlling the autosampler and the measuring instrument unit and for processing the CD spectra from the measuring instrument unit, wherein the computer includes a sequence setting function for determining the measurement order of the samples, and the sequence setting function accepts the following input information (1) to (3): (1) information about the sample, (2) information about the solvent contained in the sample, and (3) information about the number of samples (N: N is a natural number of 1 or more), A multi-sample circular dichroism analyzer characterized by obtaining attribute information (R, S1, S2, ...) that distinguishes whether the sample and the solvent relate to a standard sample (R) or to any of the samples to be evaluated (S1, S2, ...), and type information (S, B) that distinguishes the sample and the solvent, and using the following rules (4) to (6): (4) For each attribute (R, S1, S2, ...), one sample (S) and one solvent (B) are arranged as one set, with one solvent (B) sample placed immediately before or immediately after one sample (S); (5) The sets of sample (S) and solvent (B) samples for all attributes (R, S1, S2, ...) are arranged in a single row; and (6) The arrangement of the sets of samples is repeated as many times as there are samples (N) of the sample, thereby determining the measurement order of the samples.
2. The multi-sample circular dichroism measuring device according to claim 1, characterized in that the sequence setting function determines the position of the samples in the autosampler according to the following rules (7) and (8) using the attribute information (R, S1, S2, ...) and type information (S, B) in order to determine the position in which the samples are arranged in the vertical and horizontal planes of the autosampler: (7) the rows of sample sets according to rule (5) are arranged vertically, and (8) samples for which both the attribute information and the type information are the same are arranged horizontally.
3. The multi-sample circular dichroism measuring device according to claim 1, characterized in that the computer includes a storage unit capable of storing the CD spectral data with attribute information (R, S1, S2, ...) and type information (S, B) assigned to or associated with the CD spectral data, and is configured to read the CD spectral data to be processed from the storage unit using the attribute information (R, S1, S2, ...) and type information (S, B) when executing a predetermined data processing.
4. The multi-sample circular dichroism measuring device according to claim 3, characterized in that the data processing includes at least one of baseline correction, calculation between spectral data, peak detection, waveform separation, and spectral analysis.
5. The multi-sample circular dichroism analyzer according to claim 4, characterized in that the spectral analysis is for evaluating the identity or higher-order structure of a protein.