Identification of the first sample in a series of consecutive samples

Abstract

The ADE device identifies a sequence of one or more identifiable shots from at least one sample using different values or patterns of values of one or more ADE parameters. The one or more identifiable shots are performed to produce one or more mass peaks having one or more characteristic values or patterns of characteristic values that are different from other mass peaks produced. The shot times are stored. The one or more detected peaks having different characteristic values or patterns of characteristic values are identified as being produced by the one or more identifiable shots. A delay time is calculated from the time of the identifiable shots and the time of the identified detected peaks, and the peaks are aligned to the samples using the delay time, the stored times, and the sample order.

Description

[0001] Related US applications

[0002] This application claims the benefit of priority to U.S. Provisional Application No. 63 / 029,237, filed May 22, 2020, the entire contents of which are incorporated herein by reference. Technical Field

[0003] This paper teaches the operation of an acoustic droplet ejection (ADE) device (referred to as an acoustic jet mass spectrometry (AEMS) system) coupled to a mass spectrometer via an open port interface (OPI), and how to align the ejected sample with the detected mass peak. More specifically, systems and methods are provided for identifying the first sample in a sequence of one or more samples. Background Technology

[0004] Sampling time issue

[0005] As described below, an ADE device can be used to rapidly transfer samples to an Open Port Interface (OPI), which then transmits the analyte through a transfer tube to a mass spectrometer, where it is analyzed. This method of sample analysis is known as AEMS. In AEMS, there is a delay (several seconds) between the occurrence of the acoustic jet and the detection of the signal from the analyte. The time it takes for the analyte to travel from the acoustic jet to the inlet of the mass spectrometer also varies.

[0006] When using OPI in an AEMS at a high injection rate (1 sample per second), multiple diluted sample columns may travel simultaneously in the transfer tube. Identifying the first sample in the injection sequence is crucial in determining which detected signal belongs to which sample. If the signal from the first sample is lost or misidentified, there is a risk that signals from subsequent samples will be identified as originating from the first sample, leading to incorrect analyses of all subsequent samples.

[0007] Reasons why the first sample might not be detected could include, but are not limited to, the user not adding the analyte to the well, the ADE device failing to eject the droplet or ejecting it but the droplet not entering the OPI, for example due to electrostatic charge, an asymmetrical sample surface meniscus or misalignment, or air bubbles in the sample well preventing proper droplet ejection. Although signal loss from the sample may be rare, its consequences can be severe (incorrect data).

[0008] Currently, in AEMS systems, the ADE (Action Deposition and Analysis) device generates a time file that specifies the time for spraying each sample from each well. After mass spectrometry (MS) analysis, the peaks detected over time are aligned with the times in the time file to identify the sample. However, this alignment can be obscured if certain peaks are missing, especially the first or first few peaks.

[0009] As a result, additional AEMS systems and methods are needed to align the ejection time of the ADE device with the peaks detected by the mass spectrometer over time, in order to ensure that missing peaks do not cause errors in the collected data.

[0010] ADE and OPI background

[0011] The accurate determination of the presence, identification, concentration, and / or quantity of analytes in a sample is crucial in many fields. Many techniques used in this analysis involve the ionization of substances in a fluid sample before introduction into the analytical equipment employed. The choice of ionization method will depend on the nature of the sample and the analytical technique used, and many ionization methods are available. Mass spectrometry is a sophisticated analytical technique in which sample molecules are ionized and then the resulting ions are classified by their mass-to-charge ratio.

[0012] The ability to couple mass spectrometry (especially electrospray mass spectrometry) to separation techniques such as liquid chromatography (LC) including high-performance liquid chromatography (HPLC), capillary electrophoresis, or capillary electrochromatography means that complex mixtures can be separated and characterized in a single process. Improvements in HPLC system design, such as reduced dead volume and increased pump pressure, enable the benefits of smaller columns containing smaller particles, improved separation, and faster run times. Despite these improvements, the time required for sample separation remains approximately one minute. Even when true separation is not required, the mechanism of loading samples into the mass spectrometer using conventional autosamplers with some degree of cleaning between injections still limits sample loading time to approximately ten seconds per sample.

[0013] Some success has been achieved in improving throughput performance. Simplified sample preparation, using solid-phase extraction instead of conventional chromatography to remove salts, can reduce pre-injection time per sample from several minutes per sample required by HPLC to less than ten seconds. However, this increase in sampling speed comes at the cost of sensitivity. Furthermore, the time savings achieved through increased sampling speed are offset by the need for cleaning between samples.

[0014] Another limitation of current mass spectrometer loading processes is the issue of sample residues, which requires a cleaning step after loading each sample to prevent subsequent samples from being contaminated by residual analytes from previous samples. This is time-consuming and adds steps to the process, complicating rather than simplifying analyses with traditional autosampler systems.

[0015] Another limitation of current mass spectrometers when used to process complex samples, such as biological fluids, is the unwanted “matrix effect” phenomenon, which arises from the presence of matrix components (e.g., natural matrix components such as cellular matrix components, or contaminants inherent in certain materials such as plastics) and adversely affects the ability, precision, and / or accuracy of detecting analytes of interest.

[0016] A system combining an analog-to-digital converter (ADE) with an open port interface (OPI) for high-throughput mass spectrometry has been developed. This system is described in U.S. Patent Application No. 16 / 198,667 (hereinafter referred to as the “'667 application”), which is incorporated herein by reference in its entirety.

[0017] Figure 1A This is an exemplary system combining ADE and OPI, as described in application '667. Figure 1A In the diagram, the ADE device is generally displayed at position 11, spraying droplet 49 toward the continuous flow OPI generally displayed at position 51 and into its sampling end 53.

[0018] ADE device 11 includes at least one reservoir: a first reservoir and an optional second reservoir 31 are shown at 13. In some embodiments, multiple additional reservoirs may be provided. Each reservoir is configured to contain a fluid sample having a fluid surface, for example, a first fluid sample 14 and a second fluid sample 16 having fluid surfaces indicated at 17 and 19, respectively. Fluid samples 14 and 16 may be the same or different, but are typically different, to the extent that they will generally contain two different analytes intended to be transported to and detected in an analytical instrument (not shown). The analytes may be biomolecules or macromolecules other than biomolecules, or they may be small organic molecules, inorganic compounds, ionized atoms, or any part of any size, shape, or molecular structure, as explained earlier in this section. Furthermore, the analytes may be dissolved, suspended, or dispersed in the liquid component of the fluid sample.

[0019] When using more than one reservoir, such as Figure 1AAs shown, the reservoirs are preferably substantially identical and substantially acoustically indistinguishable, although identical construction is not required. As explained earlier in this section, the reservoirs can be trays, shelves, or other individual removable components of such a structure, but they can also be fixed within a plate, such as an orifice plate or another substrate. As shown, each reservoir is preferably substantially axisymmetric, having vertical walls 21 and 23 extending upward from circular reservoir bases 25 and 27 and terminating at openings 29 and 31, respectively, although other reservoir shapes and reservoir base shapes may also be used. The material and thickness of each reservoir base should allow acoustic radiation to be transmitted through it and into the fluid sample contained within each reservoir.

[0020] The ADE device 11 includes an acoustic jet 33, which includes an acoustic radiation generator 35 and a focusing device 37 for focusing the generated acoustic radiation at a focal point 47 near the fluid surface within the fluid sample. Figure 1A As shown, the focusing device 37 may comprise a single solid element having a concave surface 39 for focusing acoustic radiation; however, the focusing device may also be constructed in other ways as discussed below. Thus, the acoustic jet 33 is adapted to generate and focus acoustic radiation to eject fluid droplets from each of the fluid surfaces 17 and 19 when acoustically coupled to the reservoirs 13 and 15 and thus to the fluids 14 and 16, respectively. The acoustic radiation generator 35 and the focusing device 37 may be used as a single unit controlled by a single controller, or they may be controlled independently, depending on the desired performance of the device.

[0021] Optimally, acoustic coupling between each reservoir in the injector and reservoir is achieved through indirect contact, such as... Figure 1A As shown in the figure, the acoustic coupling medium 41 is placed between the injector 33 and the base 25 of the reservoir 13, with the injector and reservoir located at a predetermined distance from each other. The acoustic coupling medium can be an acoustic coupling fluid, preferably an acoustically homogeneous material that conformally contacts both the acoustic focusing device 37 and the underside of the reservoir. Furthermore, it is important to ensure that the fluid medium is substantially free of materials with acoustic properties different from those of the fluid medium itself. As shown, the first reservoir 13 is acoustically coupled to the acoustic focusing device 37 such that sound waves generated by the acoustic radiation generator are directed by the focusing device 37 into the acoustic coupling medium 41, which then transmits acoustic radiation into the reservoir 13. The system may comprise a single acoustic injector, such as... Figure 1A As shown in the diagram, or as mentioned earlier, it can contain multiple injectors.

[0022] In operation, in embodiments where multiple reservoirs are provided, reservoir 13 and optional reservoir 15 of the device are respectively filled with a first fluid sample 14 and a second fluid sample 16, such as... Figure 1A As shown in the diagram, the acoustic jet 33 is located directly below the reservoir 13, where acoustic coupling between the jet and the reservoir is provided via an acoustic coupling medium 41. Initially, the acoustic jet is positioned directly below the sampling end 53 of the OPI 51, such that the sampling end faces the surface 17 of the fluid sample 14 in the reservoir 13. Once the jet 33 and the reservoir 13 are properly aligned below the sampling end 53, the acoustic radiation generator 35 is activated to generate acoustic radiation, which is directed by the focusing device 37 to a focal point 47 near the fluid surface 17 of the first reservoir. As a result, droplets 49 are ejected from the fluid surface 17 toward and into the liquid boundary 50 at the sampling end 53 of the OPI 51, where they combine with the solvent in the flow probe 53.

[0023] The profile of the liquid boundary 50 at the sampling end 53 can vary from extending beyond the sampling end 53 to protruding inward into the OPI 51. In a multi-reservoir system, for example, a reservoir unit (not shown) of a multi-well plate or tube rack can then be repositioned relative to the acoustic ejector such that another reservoir is brought into alignment with the ejector and can eject droplets of the next fluid sample. The solvent in the flow probe continuously circulates through the probe, thereby minimizing or even eliminating the “residue” between droplet ejection events. The multi-well plate can be, but is not limited to, 24-well, 384-well, or 1536-well plates.

[0024] Fluid samples 14 and 16 are samples of any fluid that is intended to be delivered to the analytical instrument. Therefore, the fluid sample may contain minimal, partially or completely dissolved, dispersed, or suspended solids in the liquid, which may be an aqueous or non-aqueous liquid. The structure of one embodiment of the OPI 51 is also... Figure 1A As shown in the diagram. Other configurations of the continuous flow OPI can be used as is or with modifications, all of which are clear in the art and operate on essentially the same principles. Figure 1A As can be seen, the sampling end 53 of OPI 51 is spaced apart from the fluid surface 17 in the reservoir 13 by a gap 55. The gap 55 may be an air gap, an inert gas gap, or it may include some other gaseous material; there is no liquid bridge connecting the sampling end 53 to the fluid 14 in the reservoir 13.

[0025] OPI 51 includes a solvent inlet 57 for receiving solvent from a solvent source and a solvent delivery capillary 59 for transferring a solvent flow from the solvent inlet 57 to a sampling end 53, wherein jet droplets 49 of the fluid sample 14 containing the analyte combine with the solvent to form an analyte-solvent dilution. A solvent pump (not shown) is operatively connected to and in fluid communication with the solvent inlet 57 to control the rate of solvent flow from the solvent supply through the solvent delivery capillary to the sampling end 53, and thus also the rate of solvent flow within the solvent delivery capillary 59.

[0026] The fluid flow within OPI 51 carries the analyte-solvent diluent through the sample transfer capillary 61 provided by the inner capillary 73 toward the sample outlet 63 for subsequent delivery to the analytical instrument. A sampling pump (not shown) may be provided, operatively connected to and in fluid communication with the sample transfer capillary 61, to control the output rate from the outlet 63 and the aspiration of solvent at the sampling end 53.

[0027] In one embodiment, a positive displacement pump is used as the solvent pump, such as a peristaltic pump, and instead of a sampling pump, a suction nebulization system is used to extract the analyte-solvent diluent from the sample outlet 63 via the Venturi effect, which is caused by gas inlet 67 (in Figure 1A (Simplified form shown, to this extent the characteristics of a suction nebulizer are clear in the art) The nebulized gas flow introduced from the nebulizing gas source 65 is caused as it flows past the outside of the sample outlet 63. The analyte-solvent diluent flow is then drawn upward through the sample transport capillary 61 by the pressure drop generated as the nebulized gas passes through the sample outlet 63 and combines with the fluid leaving the sample transport capillary 61. A gas pressure regulator is used to control the rate of gas flow entering the system via the gas inlet 67.

[0028] In a preferred embodiment, the atomizing gas flows in a sheath flow pattern over the outside of the sample transfer capillary 61 at or near the sample outlet 63, wherein the analyte-solvent diluent is drawn through the sample transfer capillary 61 as it flows through the sample outlet 63, causing a suction at the sample outlet when mixed with the atomizer gas. In various embodiments, the sample outlet 63 is a straight tube protruding from the gas nozzle.

[0029] In the illustrated embodiment, the solvent transport capillary 59 and the sample transport capillary 61 are provided by an outer capillary 71 and an inner capillary 73 substantially coaxially disposed within the outer capillary 71, wherein the inner capillary 73 defines the sample transport capillary, and the annular space between the inner capillary 73 and the outer capillary 71 defines the solvent transport capillary 59. The size of the inner capillary 73 can be from 1 micrometer to 1 mm, for example, 200 micrometers. A typical outer diameter of the inner capillary 73 can be from 100 micrometers to 3 or 4 centimeters, for example, 360 micrometers. A typical inner diameter of the outer capillary 71 can be from 100 micrometers to 3 or 4 centimeters, for example, 450 micrometers. A typical outer diameter of the outer capillary 71 can be from 150 micrometers to 3 or 4 centimeters, for example, 950 micrometers.

[0030] In other embodiments, different geometries and configurations of the solvent delivery capillary and sample delivery capillary may be provided. For example, the capillaries need not be coaxial and may have different cross-sections than those illustrated, as long as they are suitable for supplying solvent to the exposed sampling area and aspirating the supplied solvent and captured sample from the sampling area for analysis by the sample analyzer. The cross-sectional regions of the inner capillary 73 and / or the outer capillary 71 may be circular, elliptical, hyperelliptical (i.e., shaped like a hyperellipse), or even polygonal. Although Figure 1A The system shown indicates that the solvent flow direction is downward from the solvent inlet 57 towards the sampling end 53 in the solvent transfer capillary 59, while the analyte-solvent diluent flow direction is upward from the sampling end 53 through the sample transfer capillary 61 towards the outlet 63. However, the directions can be reversed, and the OPI 51 does not need to be precisely vertically positioned. Figure 1A Various modifications to the structure shown will be apparent to those skilled in the art, or can be derived by those skilled in the art during use of the system.

[0031] The system may also include an adjuster 75 coupled to the outer capillary 71 and the inner capillary 73. The adjuster 75 may be adapted to move the outer capillary end 77 and the inner capillary end 79 longitudinally relative to each other. The adjuster 75 may be any device capable of moving the outer capillary 71 relative to the inner capillary 73. An exemplary adjuster 75 may be a motor, including but not limited to electric motors (e.g., AC motors, DC motors, electrostatic motors, servo motors, etc.), hydraulic motors, pneumatic motors, translation stages, and combinations thereof. As used herein, “longitudinal” refers to an axis extending along the length of OPI 51, and the inner capillary 73 and the outer capillary 71 may be arranged coaxially about the longitudinal axis of OPI 51, as shown in FIG1.

[0032] Optionally, prior to use, the regulator 75 is used to pull the inner capillary 73 longitudinally inward, causing the outer capillary 71 to protrude beyond the end of the inner capillary 73, in order to facilitate optimized fluid communication between the solvent flow in the solvent transport capillary 59 and the sample transported as the analyte-solvent dilution flow 61 in the sample transport capillary 61. Furthermore, as... Figure 1A As shown, for stability and ease of handling, OPI 51 is typically fixed within a generally cylindrical retainer 81.

[0033] Figure 1B is an exemplary embodiment of a system 110 for ionizing analytes received within the open end of a sampling OPI and performing mass analysis on the analytes, as described in application '667'. System 110 includes an acoustic droplet injection device 11 configured to inject droplets 49 from a reservoir into the open end of a sampling OPI 51. As shown in Figure 1B, the exemplary system 110 typically includes a sampling OPI 51 and a mass analyzer 170, which is in fluid communication with an atomizer-assisted ion source 160 for discharging a liquid containing one or more sample analytes (e.g., via an electrospray electrode 164) into an ionization chamber 112. The mass analyzer 170 is in fluid communication with the ionization chamber 112 for downstream processing and / or detection of ions generated by the ion source 160. Fluid handling system 140 (e.g., including one or more pumps 143 and one or more conduits) provides liquid flow from solvent reservoir 150 to sampling OPI 51 and from sampling OPI 51 to ion source 160. For example, as shown in FIG1B, solvent reservoir 150 (e.g., containing liquid, desorption solvent) can be fluidly coupled to sampling OPI 51 via supply conduit through which liquid can be delivered at a selected volumetric rate by pump 43 (e.g., reciprocating pump, positive displacement pump such as rotary pump, gear pump, plunger pump, piston pump, peristaltic pump, diaphragm pump, or other pump such as gravity pump, pulse pump, pneumatic pump, electric pump, and centrifugal pump), all of which are examples of non-limiting methods. As discussed in detail below, liquid inflow and outflow from sampling OPI 51 occur within an accessible sample space at the open end, such that one or more droplets 49 can be introduced into the liquid boundary 50 at the sampling end and subsequently delivered to ion source 160.

[0034] As shown, system 110 includes an acoustic droplet injection device 11 configured to generate acoustic energy that is applied to a liquid contained in a reservoir (such as...). Figure 1AThe liquid within (as depicted herein) causes one or more droplets 49 to be ejected from the reservoir into the open end of the sampling OPI 51. The controller 180 may be operatively coupled to the acoustic droplet injection device 11 and may be configured to operate any aspect of the acoustic droplet injection device 11 (e.g., focusing device, acoustic radiation generator, automated device for positioning one or more reservoirs in alignment with the acoustic radiation generator, etc.) to inject droplets into the sampling OPI 51, or to inject droplets substantially continuously in other ways discussed herein, or to inject droplets for selected portions of an experimental scheme given by way of non-limiting examples. The controller 180 may be, but is not limited to, a microcontroller, computer, microprocessor, the computer system of FIG. 1, or any device capable of sending and receiving control signals and data.

[0035] As shown in Figure 1B, the exemplary ion source 160 may include a source 65 of compressed gas (e.g., nitrogen, air, or an inert gas) that supplies a high-speed atomized gas stream surrounding the outlet end of the electrospray electrode 164 and interacting with the fluid exiting from the outlet end to enhance sample plume formation and ion release within the sample plume for sampling at 114b and 116b, for example, via the interaction of the high-speed atomized stream and the jet of liquid sample (e.g., analyte-solvent diluent). The nebulizer gas can be supplied at various flow rates, for example, in the range from about 0.1 L / min to about 20 L / min, which can also be controlled by the controller 180 (e.g., via opening and / or closing valve 163).

[0036] It will be understood that the flow rate of the atomizer gas can be adjusted (e.g., under the influence of the controller 180) so that the flow rate of the liquid within the sampling OPI 51 can be adjusted based on the suction / draft force generated, for example, by the interaction between the atomizer gas and the analyte-solvent diluent being discharged from the electrospray electrode 164 (e.g., due to the Venturi effect).

[0037] As shown in Figure 1B, the ionization chamber 112 can be maintained at atmospheric pressure, although in some embodiments, the ionization chamber 112 can be evacuated to a pressure below atmospheric pressure. The ionization chamber 112 is separated from the gas curtain chamber 114 by a plate 114a having a curtain plate opening 114b, within which the analyte can be ionized as the analyte-solvent diluent is discharged from the electrospray electrode 164. As shown, the vacuum chamber 116 housing the mass analyzer 170 is separated from the curtain chamber 114 by a plate 116a having a vacuum chamber sampling opening 116b. Vacuuming through one or more vacuum pump ports 118 can maintain the curtain chamber 114 and the vacuum chamber 116 at selected pressures (e.g., the same or different subatmospheric pressures, below the pressure of the ionization chamber).

[0038] Those skilled in the art will also understand, and in accordance with the teachings herein, that the mass analyzer 170 can have various configurations. Typically, the mass analyzer 170 is configured to process (e.g., filter, classify, dissociate, detect, etc.) sample ions generated by the ion source 160. By way of non-limiting example, the mass analyzer 170 can be a triple quadrupole mass spectrometer or any other mass analyzer known in the art and modified in accordance with the teachings herein. Other non-limiting exemplary mass spectrometer systems that can be modified based on various aspects of the systems, apparatus, and methods disclosed herein can be found, for example, in the article entitled “Product ion scanning using a QqQ linear iontrap (Q TRAP) mass spectrometer” written by James W. Hager and J.C.Y. Le Blanc and published in Rapid Communications in Mass Spectrometry (2003; 17: 1056-1064), and in U.S. Patent No. 7,923,681 entitled “Collision Cell for Mass Spectrometer,” which is incorporated herein by reference in its entirety.

[0039] Other configurations, including but not limited to those described herein and others known to those skilled in the art, may also be used in conjunction with the systems, apparatus, and methods disclosed herein. For example, other suitable mass spectrometers include single quadrupole, triple quadrupole, ToF, trap, and mixing analyzers. It will also be understood that any number of additional elements may be included in system 110, including, for example, an ion mobility spectrometer (e.g., a differential mobility spectrometer) disposed between ionization chamber 112 and mass analyzer 170 and configured to separate ions based on their mobility through drift gas in high and low fields rather than their mass-to-charge ratio. Furthermore, it will be understood that mass analyzer 170 may include a detector capable of detecting ions passing through analyzer 170 and may, for example, provide a signal indicating the number of ions detected per second.

[0040] Mass Spectrometry Background

[0041] Mass spectrometers are often coupled with chromatography or other sample introduction systems such as ADE devices and OPI to identify and characterize compounds of interest from a sample or to analyze multiple samples. In such coupled systems, the eluting or injected solvent is ionized, and a series of mass spectra are obtained from the eluting solvent at specific time intervals called retention times. These retention times range from, for example, 1 second to 100 minutes or more. This series of mass spectra forms a chromatogram, or extractive ion chromatography (XIC).

[0042] For example, peaks found in XIC are used to identify or characterize known peptides or compounds in a sample. More specifically, peak retention time and / or peak area are used to identify or characterize (quantify) known peptides or compounds in a sample. In cases where multiple samples are provided over time by a sample introduction device, peak retention time is used to align the peak with the correct sample.

[0043] In conventional separation-coupled mass spectrometry (SCMS) systems, fragments or product ions of known compounds are selected for analysis. Tandem mass spectrometry or mass / mass spectrometry (MS / MS) scans are then performed at each separation interval for a mass range including the product ions. The intensities of the product ions found in each MS / MS scan are collected over time and analyzed, for example, as a spectral set or XIC.

[0044] Tandem mass spectrometry, or MS / MS, is a well-known technique for analyzing compounds. Tandem mass spectrometry involves the ionization of one or more compounds from a sample, the selection of one or more precursor ions of one or more compounds, the fragmentation of one or more precursor ions into fragments or product ions, and the mass analysis of the product ions.

[0045] Tandem mass spectrometry can provide both qualitative and quantitative information. Product ion spectra can be used to identify molecules of interest. The intensities of one or more product ions can be used to quantify the amount of compounds present in a sample.

[0046] Tandem mass spectrometers can be used to perform a wide variety of experimental methods or workflows. These workflows fall into three main categories: targeted acquisition, information-dependent acquisition (IDA) or data-dependent acquisition (DDA), and data-independent acquisition (DIA).

[0047] In targeted acquisition methods, one or more transitions from a precursor ion to a product ion are predefined for the compound of interest. When the sample is introduced into a tandem mass spectrometer, these one or more transitions are interrogated or monitored during each of multiple time periods or cycles. In other words, the mass spectrometer selects and breaks down the precursor ion for each transition and performs targeted mass analysis only on the product ion of the transition. As a result, the intensity (product ion intensity) for each transition is generated. Targeted acquisition methods include, but are not limited to, multiple reaction monitoring (MRM) and selected reaction monitoring (SRM).

[0048] In targeted acquisition methods, a list of transformations is typically queried during each cycle time. To reduce the number of transformations queried at any given time, some targeted acquisition methods have been modified to include a retention time or retention time range for each transformation. Only during that retention time or within that retention time range will that specific transformation be queried. One targeted acquisition method that allows specifying retention times for transformations is called pre-scheduled MRM.

[0049] In the IDA method, users can specify standards for performing non-targeted mass analysis of product ions while introducing the sample into the tandem mass spectrometer. For example, in the IDA method, a precursor ion or mass spectrometry (MS) survey scan is performed to generate a precursor ion peak list. Users can select standards to filter the peak list of a subset of precursor ions. Then, MS / MS is performed on each precursor ion in the precursor ion subset. Product ion spectra are generated for each precursor ion. When the sample is introduced into the tandem mass spectrometer, MS / MS is repeated on the precursor ions in the precursor ion subset.

[0050] However, in proteomics and many other sample types, the complexity and dynamic range of compounds are extremely high. This poses a challenge to traditional targeting and IDA methods, thus requiring very high-speed MS / MS acquisition to deeply interrogate samples in order to both identify and quantify a wide range of analytes.

[0051] As a result, a third major class of DIA methods for tandem mass spectrometry was developed. These DIA methods have been used to increase the reproducibility and comprehensiveness of data collected from complex samples. DIA methods can also be referred to as non-specific fragmentation methods. In traditional DIA methods, the role of the tandem mass spectrometer during MS / MS scans does not vary based on data obtained from previous precursor or product ion scans. Instead, a precursor ion mass range is selected. The precursor ion mass selection window is then stepped across this range. All precursor ions within the precursor ion mass selection window are fragmented, and all product ions from all precursor ions within the window are mass-analyzed.

[0052] The precursor ion mass selection window used for scanning a range of mass can be very narrow, making it unlikely that multiple precursors will be present within the window. For example, this type of DIA method is known as MS / MS. ALL In MS / MS ALLIn this method, a precursor ion mass selection window is scanned or stepped approximately 1 amu across the entire mass range. Product ion spectra are generated for each 1 amu precursor mass window. The time taken for a single analysis or scan of the entire mass range is called a scan cycle. However, scanning a narrow precursor ion mass selection window across a wide precursor ion mass range during each cycle is not practical for some instruments and experiments.

[0053] As a result, a large precursor ion mass selection window is stepped across the entire precursor mass range, or a selection window with a large width is used. This type of DIA method is known as, for example, SWATH acquisition. In SWATH acquisition, the precursor ion mass selection window stepped across the precursor mass range in each cycle may have a width of 5-25 amu or even greater. Like MS / MS... ALL The method is the same: all precursor ions in each precursor ion mass selection window are broken down, and all product ions of all precursor ions in each mass selection window are mass analyzed. Summary of the Invention

[0054] A system, method, and computer program product for aligning a sample with peaks detected in an AEMS are disclosed. In some embodiments, a system may be provided comprising an ADE device, an OPI, an ion source device, a mass spectrometer, and a controller for coordinating the actions of the components.

[0055] An ADE (Antibody-Definition) device uses a combination of values ​​or value patterns of one or more ADE parameters that differ from the analytical sequence of sample jets for a series of samples being analyzed to perform a sequence of identifiable single or multiple jets from one or more samples in a series of samples. The ADE device performs the identifiable single or multiple jet sequence to produce one or more mass peaks having characteristic values ​​or characteristic patterns of one or more peak features that differ from the mass peaks produced by the analytical sequence for the samples being analyzed. The ADE device also stores or transmits the sample jet times corresponding to the identifiable jet sequence. The sample jet times and / or the characteristics of the identifiable single or multiple jet sequence can produce corresponding one or more identifiable mass peaks, which can be used to align subsequent analytical sequences of the mass peaks with the corresponding jetted samples.

[0056] OPI receives a sequence of identifiable single or multiple jets and other jets at the tube inlet. OPI mixes the received identifiable jets with the solvent in the tube to form a series of analyte-solvent diluents. OPI then delivers this series of diluents to the tube outlet.

[0057] An ion source device receives and ionizes the series of diluents, thereby generating an ion beam. A mass spectrometer receives the ion beam and performs mass analysis on it over time, producing a series of detected mass peaks with intensity varying with time.

[0058] The processor receives the peaks from the series and the stored sample ejection times. The processor identifies one or more detected peaks from the received series that have different characteristic values ​​or characteristic value patterns as corresponding to or generated by an identifiable ejection. The processor calculates a delay time based on the time of the identifiable ejection and the time of the identified one or more detected peaks. Finally, the processor aligns the series of detected peaks with the series of samples using the delay time, the stored time, and the order of the series of samples.

[0059] This article describes these and other characteristics of the applicant's teaching. Attached Figure Description

[0060] Those skilled in the art will understand that the accompanying drawings described below are for illustrative purposes only. The drawings are not intended to limit the scope of this teaching in any way.

[0061] Figure 1A It is an exemplary system that combines acoustic droplet ejection (ADE) with an open port interface (OPI) sampling interface, as described in '667 application.

[0062] Figure 1B is an exemplary system for ionizing analytes received within the open end of a sampling OPI and for performing quality analysis on the analytes, as described in application '667'.

[0063] Figure 2 This is a block diagram illustrating a computer system on which embodiments of this teaching can be implemented.

[0064] Figure 3 This is an exemplary drawing showing the correct alignment of the detected peak with the ejection time from the ADE device time file.

[0065] Figure 4 This is an exemplary plot showing three peaks of analytes from four different samples, sequentially supplied to the mass spectrometer by the ADE device and OPI, detected by the mass spectrometer over time.

[0066] Figure 5 It is shown Figure 4 How did the mismatch between the number of peaks detected and the number of spray times lead to four different sample sprays? Figure 4 An exemplary plot showing the different alignments of the three peaks.

[0067] Figure 6This is an exemplary plot showing the misalignment of the detected peaks with the injection time due to missing peaks and low-intensity peaks.

[0068] Figure 7 This is an exemplary plot illustrating how, according to various embodiments, the peaks detected by the mass spectrometer can be altered by changing the jetting time period of the ADE device.

[0069] Figure 8 This is an exemplary plot of an idealized detection peak according to various embodiments, the idealized detection peak including the peak and a first identifiable pattern of a blank area followed by the remaining sample peak.

[0070] Figure 9 This is an exemplary drawing illustrating a barcode or identifiable pattern template for identifying detected peaks according to various embodiments.

[0071] Figure 10 This illustrates the use of various embodiments. Figure 9 An exemplary drawing of the positions of the barcode patterns of the peaks detected in the remaining samples of the template, and the two peaks detected in the two samples.

[0072] Figure 11 This illustrates various embodiments of the relationship with Figure 10 An exemplary plot of the same data but drawn relative to a lower intensity range, so as to see Figure 10 Two barcode patterns.

[0073] Figure 12 This is a schematic diagram of a system for aligning a sample with peaks detected in an AEMS, according to various embodiments.

[0074] Figure 13 This is a flowchart illustrating a method for aligning a sample with peaks detected in AEMS according to various embodiments.

[0075] Figure 14 This is a schematic diagram of a system comprising one or more different software modules according to various embodiments, the system performing a method for aligning a sample with peaks detected in AEMS.

[0076] Before describing one or more embodiments of this teaching in detail, those skilled in the art will understand that this teaching is not limited to its application in the details of the construction, arrangement of components, and arrangement of steps set forth in the following detailed description or illustrated in the accompanying drawings. Furthermore, it is to be understood that the wording and terminology used herein are for descriptive purposes and should not be considered limiting. Detailed Implementation

[0077] Computer-implemented systems

[0078] Figure 2 This is a block diagram illustrating a computer system 200 on which embodiments of this teaching can be implemented. The computer system 200 includes a bus 202 or other communication mechanism for transmitting information, and a processor 204 coupled to the bus 202 for processing information. The computer system 200 also includes a memory 206, which may be random access memory (RAM) or other dynamic storage device, coupled to the bus 202 for storing instructions to be executed by the processor 204. The memory 206 may also be used to store temporary variables or other intermediate information during the execution of instructions to be executed by the processor 204. The computer system 200 also includes a read-only memory (ROM) 208 or other static storage device coupled to the bus 202 for storing instructions and static information for the processor 204. A storage device 210, such as a disk or optical disk, is provided and coupled to the bus 202 for storing information and instructions.

[0079] Computer system 200 can be coupled via bus 202 to display 212, such as a cathode ray tube (CRT) or liquid crystal display (LCD), for displaying information to the computer user. Input device 214, including alphanumeric keys and other keys, is coupled to bus 202 for transmitting information and command selections to processor 204. Another type of user input device is cursor controller 216, such as a mouse, trackball, or cursor arrow keys, for transmitting directional information and command selections to processor 204 and for controlling cursor movement on display 212. Such input devices typically have two degrees of freedom on two axes, namely a first axis (x) and a second axis (y), which allows the device to specify a position in a plane.

[0080] Computer system 200 can execute this teaching. Consistent with certain embodiments of this teaching, results are provided by computer system 200 in response to processor 204 executing one or more sequences of one or more instructions contained in memory 206. Such instructions may be read into memory 206 from another computer-readable medium, such as storage device 210. Execution of the sequence of instructions contained in memory 206 causes processor 204 to perform the processes described herein. Alternatively, this teaching may be implemented using hardwired circuitry in place of or in combination with software instructions. Therefore, implementation of this teaching is not limited to any particular combination of hardware circuitry and software.

[0081] In various embodiments, computer system 200 may be connected across a network to one or more other computer systems like computer system 200 to form a networked system. The network may include a private network or a public network such as the Internet. In a networked system, one or more computer systems may store data and provide data to other computer systems. In a cloud computing scenario, the one or more computer systems that store and provide data may be referred to as servers or the cloud. For example, one or more computer systems may include one or more web servers. For example, other computer systems that send data to and receive data from servers or the cloud may be referred to as clients or cloud devices.

[0082] As used herein, the term "computer-readable medium" refers to any medium that participates in providing instructions to processor 204 for execution. Such media can take many forms, including but not limited to non-volatile media, volatile media, and transmission media. Non-volatile media include, for example, optical discs or magnetic disks, such as storage device 210. Volatile media include dynamic memory, such as memory 206. Transmission media include coaxial cables, copper wires, and optical fibers, including the lines constituting bus 202.

[0083] Common forms of computer-readable media or computer program products include, for example, floppy disks, hard disks, magnetic tapes or any other magnetic media, CD-ROMs, digital video discs (DVDs), Blu-ray discs, any other optical media, thumb drives, memory cards, RAM, PROMs and EPROMs, FLASH-EPROMs, any other memory chips or cassette tapes, or any other tangible media from which a computer can read.

[0084] Various forms of computer-readable media may involve transmitting one or more sequences of one or more instructions to processor 204 for execution. For example, the instructions may initially be carried on a disk of a remote computer. The remote computer may load the instructions into its dynamic memory and transmit the instructions over a telephone line using a modem. A modem local to computer system 200 may receive data over the telephone line and use an infrared transmitter to convert the data into an infrared signal. An infrared detector coupled to bus 202 may receive the data carried in the infrared signal and place the data on bus 202. Bus 202 carries the data to memory 206, from which processor 204 retrieves and executes the instructions. The instructions received by memory 206 may optionally be stored on storage device 210 before or after execution by processor 204.

[0085] According to various embodiments, instructions configured to be executed by a processor to perform a method are stored on a computer-readable medium. The computer-readable medium may be a device for storing digital information. For example, a computer-readable medium includes an optical disc read-only memory (CD-ROM) known in the art for storing software. The computer-readable medium is accessed by a processor adapted to execute the instructions configured to be executed.

[0086] For illustrative and descriptive purposes, various implementations of this teaching are presented in the following description. This is not exhaustive and does not limit this teaching to the precise form disclosed. Modifications and variations are possible based on the above teaching, or may be derived from practice of this teaching. Furthermore, the described implementations include software, but this teaching can be implemented as a combination of hardware and software or as hardware alone. This teaching can be implemented using both object-oriented and non-object-oriented programming systems.

[0087] Recognizable acoustic jets for time alignment

[0088] As mentioned above, in current AEMS systems, the ADE device includes a time file specifying the time for spraying each sample from each well. After MS analysis, the peaks detected over time are aligned with the time file.

[0089] Figure 3 This is an exemplary plot 300 showing the correct alignment of detected peaks with the ejection times from an ADE device time file. In plot 300, for example, peaks 311, 312, 313, 314, and 315, with intensity relative to time, are correctly aligned with the ejection times depicted by arrows 321, 322, 323, 324, and 325, respectively.

[0090] However, if some peaks are missing, especially the first or first few peaks, this alignment can be confused.

[0091] Figure 4 This is an exemplary plot 400 showing three peaks of analytes from four different samples sequentially supplied to the mass spectrometer by the ADE device and the OPI, detected by the mass spectrometer over time. In plot 400, peaks 412, 413, and 414, representing the intensities of three different samples ejected into the OPI by the ADE device, are detected by the mass spectrometer as a function of time. At time 411, the peak of the fourth sample is missing; this is the first sample that the ADE device attempts to eject into the OPI.

[0092] Arrows 421, 422, 423, and 424 show the ejection times of peaks 412, 413, and 414 relative to time for four different samples. In other words, the positions of peaks 412, 413, and 414 relative to time for arrows 421, 422, 423, and 424 indicate the time delay between sample ejection through the ADE device and sample analysis by the mass spectrometer. Plot 400 shows that, due to the time delay between sample ejection and analysis, arrows 421, 422, 423, and 424 must be aligned with peaks 412, 413, and 414 to determine the sample corresponding to each peak. For example, the ejection times depicted by arrows 421, 422, 423, and 424 are stored in the time file by the ADE device.

[0093] Figure 5 It is shown Figure 4 How did the mismatch between the number of peaks detected and the number of spray times lead to four different sample sprays? Figure 4 Exemplary plot 500 showing different alignments of the three peaks. In alignment 510, the ejection times depicted by arrows 422, 423, and 424 are aligned with peaks 412, 413, and 414, respectively. However, in alignment 520, the ejection times depicted by arrows 421, 422, and 423 are aligned with peaks 412, 413, and 414, respectively. Both alignments are possible.

[0094] As a result, plot 500 shows that the sample identification corresponding to peaks 412, 413, and 414 is confused by the missing peak at time 411. In other words, the missing peak at time 411 makes it difficult to identify peaks 412, 413, and 414, which may lead to incorrect results for the four samples and all samples after them.

[0095] Figure 6 This is an exemplary plot 600 illustrating the misalignment of detected peaks with the injection time due to missing peaks and low-intensity peaks. In plot 600, a missing peak is present at time 610, and a low-intensity peak is present at time 620 relative to the other detected peaks. As a result, the alignment of the injection times, indicated by arrow 630, is misaligned or offset between two samples or wells. Therefore, due to the misalignment, the data reported for all 24 wells are incorrect.

[0096] Figure 4 , Figure 5 and Figure 6 This demonstrates the need for additional AEMS systems and methods to align the ejection time of the ADE device with the peaks detected by the mass spectrometer over time, ensuring that missing peaks do not introduce errors in the collected data.

[0097] In various embodiments, during experiments with numerous sample jets, the ADE device is operated to perform one or more sequences of identifiable jets against one or more samples, which are identifiable compared to jets performed against all other samples. Identifiable jets are performed to produce one or more peaks that are identifiable compared to all other peaks detected by the mass spectrometer. The sequence of one or more identifiable jets can be distinguished from subsequent analytical jet sequences based on many different characteristics of the jets performed by the ADE.

[0098] By aligning the time of the identifiable ejection from the ADE device with the time of one or more identifiable peaks from the mass spectrometer, all other ejection times and detected peaks are subsequently correctly aligned. It will be understood by those skilled in the art that the use of the terms “operated” or “operation” in relation to a device or structure is equivalent to the use of the term “suitable” or any other term that describes the functional purpose of the device or structure.

[0099] In various embodiments, the identifiable sequence includes temporal information that can be used to correlate the time of the sequence for analysis. In these embodiments, the identifiable spray can be performed at any time during the sample spraying process. In other words, the identifiable spray can be performed on one or more samples at the beginning, middle, or end of the sample spraying process. If alignment is performed after data acquisition, then the timing of the identifiable spray is not important. For example, if the identifiable spray is performed on the last sample, then if the last sample is aligned, all other samples will be correctly aligned.

[0100] However, in various other embodiments, identifiable sprays are performed on the first or first few samples. One advantage of performing identifiable sprays on the first or first few samples is the ability to use delay information in real time. For example, if identifiable sprays are performed on the first or first few samples, the delay time generated by the OPI is immediately known and can be used by the mass spectrometer for the remaining samples.

[0101] In various embodiments, a recognizable jet is performed on the first or first few samples, and the mass spectrometer uses a delay time found by aligning one or more detected peaks with the recognizable jet to modify the targeted acquisition method for all subsequent samples in real time. As described above, in some targeted acquisition methods such as pre-sequential MRM, a retention time or retention time range is provided for each transition. A particular transition is only queried within that retention time or range. Due to the variability of the delay time of OPI, the retention time or retention time range of pre-sequential MRM transitions, for example, used in AEMS, may need to be changed in real time. By using a recognizable jet on the first or first few samples, the exact delay time can be found. This delay time can then be fed back to the mass spectrometer for use in correcting the retention time or retention range of subsequent pre-sequential MRM transitions. Therefore, one or more operating parameters of the mass spectrometer can be adjusted based on information derived from the detected recognizable sequence.

[0102] As described above, compared to other jets, recognizable jets can be created using different values ​​or value patterns of one or more ADE parameters. These one or more ADE parameters may include, but are not limited to, one or more of jet duration, jet rate, and droplet volume.

[0103] For example, and in various embodiments, the simplest identifiable spray is generated by using a single sample spray time that is wider or narrower than the spray time used for any other sample. In various alternative embodiments, an identifiable spray can be generated by spraying a single sample using an identifiable pattern of spray time periods. Furthermore, an identifiable pattern of spray time periods can also be applied across two or more samples. An identifiable pattern of spray time periods can also include blank areas during which no spraying occurs.

[0104] Figure 7 This is an exemplary plot 700 illustrating how peaks detected by a mass spectrometer can be altered by varying the ejection time interval of the ADE device according to various embodiments. In plot 700, peak 710 represents the ejection of a single droplet. Peak 720 represents the ejection of 10 droplets per second over a five-second time interval. Peak 730 represents the ejection of 10 droplets per second over a 30-second time interval. Peak 740 represents the ejection of 10 droplets per second over a one-minute time interval.

[0105] In plot 700, a recognizable detection peak width is created by varying the time period in which a sufficiently high droplet rate is applied. A sufficiently high droplet rate is a droplet rate faster than the baseline width of a single droplet in order to create a single, wider detection peak. In other words, plot 700 shows that the width of the detection peak can be altered by changing the duration of the jetting process.

[0106] The comparison of peaks 710 and 720 also shows that both peak intensity and peak width can be affected by changing the injection time period. For example, the comparison of peaks 710 and 720 shows that increasing the injection time period can increase the detected peak intensity. The comparison of peaks 710, 720, 730, and 740 shows that increasing the injection time period can also increase the detected peak width.

[0107] In alternative embodiments, peak intensity and peak width can also be altered by changing the droplet volume. However, unfortunately, in the current system, the range of droplet volumes that can be varied is far more limited than the time period during which the droplets can be ejected.

[0108] Figure 700 shows that applying a identifiable jet to a sample from a single well can produce a detection peak with an identifiable detection peak. For example, the jetting time period of peak 730 can be used for one sample, while the jetting time period of peak 720 can be used for all other peaks. In other words, a single identifiable peak or peak width can be used to align the jetting time with the detected peak.

[0109] In various alternative embodiments, identifiable patterns from two or more injection time periods are used to generate identifiable patterns or codes for the detected peaks. In various embodiments, identifiable patterns can be generated from a single sample. In various alternative embodiments, identifiable patterns can be generated from two or more samples.

[0110] In various embodiments, the identifiable pattern can be a barcode on one or more sample plates. By applying specific barcode signals to data from a particular sample plate, plate traceability of the data can be enhanced. This approach can provide enhanced data security, as well as increased confidence in clinical outcomes. For example, such a scheme is important for highly regulated markets.

[0111] In some embodiments, the identifiable pattern may include a unique pattern that identifies information about the jet sequence. In some embodiments, the identifiable pattern may include a repeatable pattern that can be distinguished from the analytical jet sequence. In some aspects, the identifiable pattern may be repeated, for example, at the beginning of each row of a sample well plate, or framing the beginning and end of the analytical sequence. In some aspects, the identifiable pattern may be repeated once or more throughout the analytical sequence to ensure that time has been maintained and the expected number of analytical samples has been captured for quality analysis.

[0112] In various embodiments, the identifiable pattern may include information. For example, the identifiable pattern may be an encoding of the number of samples to be analyzed from the plate.

[0113] Similarly, identifiable patterns can be generated for any sample or any group of samples from the entire number of samples analyzed. In one embodiment, an identifiable pattern is generated for the first sample or the first two or more samples for the reasons described above and at least the following reasons.

[0114] For example, introducing a recognizable pattern for the spraying time period of the first sample ensures robust detection of that first sample. The interval between the recognizable pattern of acoustic sample spraying and the spraying of the first sample is analogous to a barcode pattern of dark and white bars. Once the first sample is robustly identified from the recognizable pattern, the processing of peaks from subsequent sample detections can be easily accomplished by knowing when the acoustic device sprayed these samples. If the detection of the first sample (using the barcode pattern) fails, it is immediately known that there is a problem with the plate, and the processing of the remaining samples can be stopped, thus saving resources and preventing inaccurate information. This barcode pattern can be recognizable and robust to a single failure event.

[0115] Figure 8 An exemplary plot 800 of idealized detected peaks according to various embodiments includes a first identifiable pattern of peaks and blank areas following the peaks of the remaining samples. In plot 800, the identifiable pattern or barcode of the first sample includes a blank area 811 preceding the first sample, an identifiable detected peak barcode 812 of the first sample, and a blank area 813 between the first sample and the remaining samples. The remaining samples 820 do not include the identifiable pattern or barcode of the first sample.

[0116] Note that the dark areas or peaks are generated by acoustically ejecting the sample. Also note that the width and height of the peaks can be varied using acoustic parameters such as ejection rate, ejection time duration, and droplet volume. For example, identifiable blank areas are created by leaving a longer gap between acoustic ejection events than the normal gap.

[0117] In various embodiments, the barcode pattern does not need to interfere with normal data processing. The barcode data can be stored in the raw data file and never displayed to the user. The user then only sees the separate data or the processed data (a table of numbers).

[0118] Similarly, in various embodiments, the barcode pattern can be placed at other locations within the board being read to ensure data alignment. Furthermore, in various embodiments, the identifiable barcode can be used in more than one place. For example, an identifiable barcode can be used on the first hole, and another identifiable barcode can be used on the last hole in the board sequence as a "bookending" to ensure alignment throughout the board. In various embodiments, these two identifiable barcodes can be the same barcode.

[0119] In various embodiments, the barcode does not necessarily have to be applied to the first well analyzed. If the user runs a standard curve, wells with high signals are typically run after wells with lower signals. As a result, the barcode can be applied to wells with good signals. Knowing which well is used as the barcode marking well allows for the alignment of the plate sample, or it can be determined that alignment was unsuccessful.

[0120] Figure 9 This is an exemplary drawing 900 illustrating a template of an identifiable pattern or barcode for identifying a detected peak according to various embodiments. If the barcode pattern is applied to the first sample, the time range in which the barcode pattern will appear is known. Based on the expected variability of flow rate and transit time, this time range or window is, for example, between two and 12 seconds after the injection time.

[0121] During this timeframe, templates are applied to locate identifiable barcode patterns. The templates include shaded areas A, B, C, and D. The templates are generated using the same cycle time as the MS data. Note that for pre-arranged MRM or Time-of-Flight (TOF) quality analyzers where cycle times vary, this template-based technique will need to be modified to account for the varying cycle times.

[0122] The method begins by moving the template across each data point detected by the mass spectrometer and calculating the minimum intensity of region A and the maximum intensity of each of regions C and D. A possible barcode pattern has been detected if the intensity of region A is greater than that of region B, region A is greater than that of region C, region B is greater than that of region D, and region C is greater than that of region D.

[0123] If a possible barcode pattern is detected, the widths of peaks A, B, and C are measured. The width of A must be greater than the width of B and greater than the width of C. If this condition is met, the barcode pattern is verified.

[0124] Note that using templates is just one method for identifying recognizable patterns. Other methods include, but are not limited to, true peak detection with width and height measurements.

[0125] In various embodiments, more than one barcode pattern may exist. If two barcode patterns are found, the distance between them is measured. This distance must match the time between barcode injections recorded in the ADE device's time file. Furthermore, no detection peak with an intensity higher than the lowest intensity of the two barcode patterns should be found before the first barcode pattern or after the last barcode pattern. If two barcode patterns meet these additional conditions, the barcode pattern is also verified.

[0126] Figure 10 This illustrates the use of various embodiments. Figure 9 An exemplary plot 1000 shows the positions of the detection peaks of the remaining samples of the template, and the positions of the barcode patterns of the two detection peaks of the two samples. In plot 1000, box 1010 marks the position of the first barcode pattern, and box 1020 marks the position of the second barcode pattern. However, since the intensity of the detection peak of the barcode pattern is much lower than the intensity of the detection peaks of the other samples, the two detection barcode patterns cannot be seen in plot 1000.

[0127] Figure 11 This illustrates various embodiments of the relationship with Figure 10 Example plot 1100, using the same data but drawn with respect to a lower intensity range, is shown in order to see... Figure 10 Two barcode patterns are shown. In drawing 1100, box 1010 marks the location of the first barcode pattern, and box 1020 marks the location of the second barcode pattern. However, the detection peaks of these barcode patterns can now be seen. For example, peaks 1111, 1112, and 1113 provide the dark areas of the first barcode pattern, and peaks 1121, 1122, and 1123 provide the dark areas of the last barcode pattern. Note that these barcode patterns are related to... Figure 8 and Figure 9 The same as shown.

[0128] A system for aligning samples with detection peaks.

[0129] Figure 12 This is a schematic diagram 1200 of a system for aligning a sample with peaks detected in an AEMS according to various embodiments. Figure 12 The system includes an ADE device 1210, an OPI device 1220, an ion source device 1230, a mass spectrometer 1240, and a processor 1250.

[0130] ADE device 1210 performs a recognizable jet for one or more samples in a series of samples 1211 using values ​​or value patterns of one or more ADE parameters that are different from those performed for other jets in a series of samples 1211. ADE device 1210 performs the recognizable jet to produce one or more mass peaks having characteristic values ​​or characteristic value patterns that are different from those produced for other samples. ADE device 1210 stores the sample jet timestamps 1212. ADE device 1210 may be, for example... Figure 1A ADE device 11.

[0131] return Figure 12The OPI 1220 receives identifiable jets and other jets at the inlet 1221 of tube 1222. The OPI 1220 mixes the received jets with the solvent in tube 1222 to form a series of analyte-solvent diluents. The OPI 1220 delivers this series of diluents to the outlet 1223 of tube 1222. The OPI 1220 can be, for example... Figure 1A OPI 51.

[0132] return Figure 12 The ion source device 1230 receives and ionizes the series of diluents, thereby generating an ion beam. For example, the ion source device 1230 can be an electrospray ionization (ESI) device. The ion source device 1230 in... Figure 12 It is shown as part of mass spectrometer 1240, but it can also be a standalone device.

[0133] Mass spectrometer 1240 receives an ion beam and performs mass analysis on the ion beam over time, thereby generating a series of detected mass peaks 1241 with intensity varying with time. Mass spectrometer 1240 can perform MS or MS / MS. Mass spectrometer 1240 can be any type of mass spectrometer. Mass spectrometer 1240 is shown as including a time-of-flight (TOF) mass analyzer, but mass spectrometer 1240 can include any type of mass analyzer.

[0134] Processor 1250 receives peaks from a series of peaks 1241 and stored sample ejection times 1212. Processor 1250 identifies one or more detected peaks from the received series of peaks 1241 that have different characteristic values ​​or characteristic value patterns as corresponding to or generated by an identifiable ejection. Processor 1250 calculates a delay time 1252 based on the identifiable ejection time and the times of the identified one or more detected peaks 1251. Finally, processor 1250 aligns the series of detected peaks 1241 with the series of samples 1211 using the delay time 1252, the stored time 1212, and the order of the series of samples 1211.

[0135] In various embodiments, processor 1250 calculates delay time 1252 based on the difference between the time of the identifiable jet and the time of one or more detected peaks 1251. In various other embodiments, processor 1250 calculates delay time 1252 by shifting the time of the identifiable jet until it matches the time of one or more detected peaks 1251.

[0136] In various embodiments, one or more ADE parameters may include one or more of the jetting time period, jetting rate, and droplet volume. In other words, ADE device 1210 uses different values ​​or value patterns of one or more of the jetting time period, jetting rate, and droplet volume to perform identifiable jetting on one or more samples in a series of samples 1211.

[0137] In various embodiments, one or more peak features may include one or more of peak width, peak intensity, and time distance to adjacent peaks. In other words, the ADE device 1210 performs identifiable jetting on one or more samples in a series of samples 1211 to generate one or more mass peaks having different characteristic values ​​or characteristic patterns of one or more of peak width, peak intensity, and time distance to adjacent peaks.

[0138] In various embodiments, different patterns of feature values ​​may include barcodes. In other words, Figure 12 The different feature patterns of one or more detected peaks 1251 identified in the sample can be like... Figure 8 The barcode in the sample includes a blank area 811 before the first sample, an identifiable detection peak barcode 812 for the first sample, and a blank area 813 between the first sample and the remaining samples.

[0139] return Figure 12 In various embodiments, the barcode may include a barcode for holding a plate of samples 1211.

[0140] In various embodiments, the barcode may include encoding information. For example, the encoding information may include the number or count of samples in a series of samples 1211.

[0141] In various embodiments, one or more samples may include the first or first plurality of samples in a series of samples 1211. In other words, the ADE device 1210 performs identifiable spraying on the first or first plurality of samples in a series of samples 1211.

[0142] In various embodiments, one or more samples may include one or more samples from a series of samples other than the first or first plurality of samples in the series of samples 1211. In other words, the ADE device 1210 performs identifiable spraying on one or more samples that are not the first or first plurality of samples in the series of samples 1211.

[0143] In various embodiments, processor 1250 receives peaks from a series of peaks 1241 and stored sample ejection times 1212 after all peaks are acquired by mass spectrometer 1240. As a result, processor 1250 analyzes the series of peaks 1241 in a post-processing step.

[0144] In various embodiments, processor 1250 analyzes a series of peaks 1241 in real time upon receiving each peak. If ADE device 1210 performs a recognizable jet for the first or first few samples in a series of samples 1211, the processor can calculate the delay time 1252 in real time and provide it as feedback to mass spectrometer 1240. Mass spectrometer 1240 can then use the delay time 1252 to correct or refine experimental parameters.

[0145] For example, processor 1250 further receives peaks from a series of peaks 1241 in real time while the mass spectrometer 1240 detects the received peaks. Processor 1250 receives the stored sample ejection time 1212 in real time while performing sample ejection and storing the ejection time. Processor 1250 identifies one or more detected peaks with different characteristic values ​​or characteristic value patterns in real time as corresponding to or generated by an identifiable ejection. Processor 1250 calculates a delay time 1252 in real time based on the time of the identifiable ejection and the time of the identified one or more detected peaks 1251. Processor 1250 instructs mass spectrometer 1240 to recalculate the values ​​of one or more experimental parameters for mass analysis using the delay time 1252.

[0146] In various embodiments, one or more experimental parameters may include retention time or collision energy of a pre-arranged mass analysis (pre-arranged MRM). For example, delay time 1252 may be used to recalculate the retention time of one or more transitions in a pre-arranged MRM experiment.

[0147] In various embodiments, when the ADE device 1210 performs an identifiable spray on the first or first few samples in a series of samples 1211, it can also perform an additional set of identifiable sprays on the last or subsequent samples in the series of samples 1211. This provides markers to define the beginning and end of the series of samples 1211.

[0148] For example, the ADE device 1210 also performs an additional set of identifiable sprays for the last or subsequent samples in a series of samples 1211. The processor 1250 then further identifies one or more peaks detected by the additional set, which have different eigenvalues ​​or eigenvalue patterns, as corresponding to or generated by the additional set of identifiable sprays. The processor 1250 further uses the timing of the peaks detected by the additional set to identify the end of the series of samples 1211.

[0149] In various embodiments, processor 1250 uses templates of different feature value patterns to identify one or more detected peaks with different feature value patterns in the received peaks 1241. For example, a template of an identifiable pattern or barcode used to identify the detected peaks is... Figure 9 As shown in the image.

[0150] In various embodiments, processor 1250 is used to send instructions, control signals, and data to and receive instructions, control signals, and data from ADE device 1210, OPI 1220, ion source device 1230, and mass spectrometer 1240. Processor 1250 controls or provides instructions, for example, by controlling one or more voltage, current, or pressure sources (not shown). Processor 1250 may be as follows: Figure 12 The individual devices shown may be processors or controllers of ADE device 1210, OPI 1220, ion source device 1230, or mass spectrometer 1240. Processor 1250 may be, but is not limited to, a controller, computer, microprocessor, etc. Figure 2 A computer system, or any device capable of sending and receiving control signals and data and analyzing the data.

[0151] Methods for aligning samples with detection peaks

[0152] Figure 13 This is a flowchart illustrating a method 1300 for aligning a sample with peaks detected in AEMS according to various embodiments.

[0153] In step 1310 of method 1300, an identifiable spray is performed on one or more samples in a series of samples using an ADE device, employing one or more ADE parameters with values ​​or value patterns different from those of other sprays performed on other samples in the series. The identifiable spray is performed to produce one or more mass peaks having characteristic values ​​or characteristic value patterns of one or more peak characteristics different from those produced for other samples. The ADE device is used to store the sample spray times.

[0154] In step 1320, identifiable jets and other jets are received at the tube inlet using an OPI. The received jets are then mixed with the solvent in the tube using an OPI to form a series of analyte-solvent diluents. Finally, this series of diluents is delivered to the tube outlet using an OPI.

[0155] In step 1330, the series of diluents are received and ionized using an ion source device to generate an ion beam.

[0156] In step 1340, a mass spectrometer is used to receive the ion beam and perform mass analysis on the ion beam over time, thereby generating a series of detected mass peaks with intensity over time.

[0157] In step 1350, the processor is used to receive the peaks in a series of peaks and the stored sample ejection time.

[0158] In step 1360, the processor is used to identify one or more detected peaks in the received peaks that have different characteristic values ​​or characteristic value patterns as being generated by identifiable jets.

[0159] In step 1370, the processor calculates the delay time based on the time of the identifiable jet and the time of one or more detected peaks.

[0160] In step 1380, the processor uses the delay time, the storage time, and the order of the series of samples to align the peaks detected in the series with the series of samples.

[0161] Computer program products used to align samples with detection peaks.

[0162] In various embodiments, the computer program product includes a tangible computer-readable storage medium containing a program having instructions that execute on a processor to perform a method for aligning a sample with peaks detected in an AEMS. This method is performed by a system comprising one or more different software modules.

[0163] Figure 14 This is a schematic diagram of a system 1400 comprising one or more different software modules according to various embodiments, the system 1400 performing a method for aligning a sample with peaks detected in an AEMS. The system 1400 includes a control module 1410 and an analysis module 1420.

[0164] Control module 1410 instructs the ADE device to perform a recognizable spray on one or more samples in a series of samples, using values ​​or value patterns of one or more ADE parameters that differ from those of other sprays performed on other samples in the series. The recognizable spray is performed to generate one or more mass peaks having characteristic values ​​or characteristic value patterns of one or more peak characteristics that differ from those generated for other samples. Control module 1410 also instructs the ADE device to store the sample spray times.

[0165] Control module 1410 instructs OPI to receive identifiable jets and other jets at the tube inlet. Control module 1410 instructs OPI to mix the received jets with the solvent in the tube to form a series of analyte-solvent diluents. Finally, control module 1410 instructs OPI to deliver this series of diluents to the tube outlet.

[0166] Control module 1410 instructs the ion source device to receive and ionize the series of diluents, thereby generating an ion beam. Control module 1410 instructs the mass spectrometer to receive the ion beam and perform mass analysis on the ion beam over time, thereby generating a series of detected mass peaks with intensity relative to time.

[0167] Analysis module 1420 receives peaks from a series of peaks and stored sample ejection times. Analysis module 1420 identifies one or more detected peaks with different characteristic values ​​or characteristic value patterns from the received peaks as corresponding to or generated by an identifiable ejection. Analysis module 1420 calculates a delay time based on the time of the identifiable ejection and the time of the identified one or more detected peaks. Finally, analysis module 1420 aligns the detected peaks in the series with the series of samples using the delay time, the stored time, and the order of the samples.

[0168] Furthermore, in describing various embodiments, the specification may have presented methods and / or processes as specific sequences of steps. However, the method or process should not be limited to the specific sequence of steps described herein, to the extent that it does not depend on the specific order of steps. Other sequences of steps may be possible, as will be understood by those skilled in the art. Therefore, the specific order of steps set forth in the specification should not be construed as a limitation of the claims. Moreover, claims relating to the method and / or process should not be limited to performing the steps in the written order, and those skilled in the art will readily understand that the order can be changed while still remaining within the spirit and scope of the various embodiments.

Claims

1. A system for identifying the first sample in an analytical sequence of one or more analytical samples to be analyzed, comprising: An acoustic droplet ejection device (ADE) is operable to eject a sample from one or more sample orifices; An open port interface, operable to receive the ejected sample and transmit the received sample to a quality analyzer; A quality analyzer, which is operable to perform quality analysis on a sample to produce a representative quality peak; and, A controller, comprising at least a processor, operable to direct the ADE jet from a sequence of identifiable single or multiple jets from a sample well prior to initiating the jetting of an analytical sequence for the one or more analytical samples, wherein the sequence of identifiable single or multiple jets is distinguishable from the jetting of subsequent analytical sequences.

2. The system according to claim 1, wherein, The open port interface can also be operated to mix the received sample with a solvent and transmit the diluted sample to the quality analyzer.

3. The system according to claim 1 or claim 2, wherein, The identifiable sequence of one or more sprays is generated by changing one or more ADE parameters of the ADE.

4. The system according to claim 1 or claim 2, wherein, The identifiable sequence also includes time information indicating the start time of the analyzed sequence.

5. The system according to claim 1 or claim 2, wherein, The mass analyzer is operable to generate a series of detected mass peaks with intensity over time, and the controller is also operable to: Receive a series of peaks corresponding to the identifiable sequence and the analyzed sequence; One or more detected peaks from the received peaks are identified as corresponding to the identifiable sequence; The start time of the analysis sequence is indicated based on the peak generation time information of the one or more detections; and, The start time is used to align the peak series of the analysis with the analytical sequence of the sample.

6. The system according to claim 1 or claim 2, wherein, The one or more ADE parameters include one or more of the following: jetting time period, jetting rate, and droplet volume.

7. The system according to claim 1 or claim 2, wherein, Identifiable sequences can be identified based on one or more peak features.

8. The system according to claim 7, wherein, Peak characteristics include one or more of the following: peak width, peak intensity, and time distance to adjacent peaks.

9. The system according to claim 1 or claim 2, wherein, Recognizable sequences can be identified based on different feature value patterns.

10. The system according to claim 9, wherein, Different patterns include barcodes.

11. The system according to claim 10, wherein, The barcode includes a barcode for a plate that holds a series of samples.

12. The system according to claim 10 or claim 11, wherein, The barcode includes encoded information.

13. The system according to claim 12, wherein, The encoded information includes the count of samples in the analyzed sequence.

14. The system according to claim 1, wherein, The controller also performs the following operations: When a peak is detected by the mass spectrometer, the peak of a series of peaks is received in real time, and the time of sample ejection from the ADE is received during sample ejection. Real-time identification of identifiable sequences. The delay time is calculated based on the time of the identifiable sequence and the time of the analyzed sequence, and The quality analyzer is instructed to perform quality analysis on the analysis sequence based on the calculated delay time.

15. The system of claim 14, wherein the instructions include recalculating the values ​​of one or more experimental parameters of the quality analysis based on the delay time.

16. The system of claim 15, wherein the one or more experimental parameters include retention time or collision energy.

17. A system for aligning a sample with peaks detected in acoustic jet mass spectrometry (AEMS), comprising: An acoustic droplet ejection ADE device, wherein the ADE device uses one or more ADE parameters of different values ​​or value patterns than other ejections performed on other samples in a series of samples to perform identifiable ejections to produce one or more mass peaks having one or more peak characteristics that are different from the mass peaks produced for other samples, and stores the sample ejection time. An open port interface receives the identifiable jet and the other jets at the inlet of the tube, mixes the received jets with the solvent in the tube to form a series of analyte-solvent diluents, and delivers the series of diluents to the outlet of the tube; An ion source device that receives and ionizes the series of diluents to generate an ion beam; A mass spectrometer that receives the ion beam and performs mass analysis on the ion beam over time, thereby generating a series of detected mass peaks with intensity relative to time; and The processor performs the following operations: Receive the peaks from a series of peaks and the stored sample ejection time. Identify one or more detected peaks with different characteristic values ​​or characteristic value patterns generated by the identifiable jet in the received peaks. The delay time is calculated based on the time of the identifiable injection and the time of one or more detected peaks. By using the delay time, storage time, and the order of the series of samples, a series of detected peaks are aligned with the series of samples.

18. The system according to claim 17, wherein, The one or more ADE parameters include one or more of the following: jetting time period, jetting rate, and droplet volume.

19. The system according to claim 17 or claim 18, wherein, The one or more peak characteristics include one or more of the following: peak width, peak intensity, and time distance to adjacent peaks.

20. The system according to claim 17 or claim 18, wherein, Different feature value patterns include barcodes.

21. The system according to claim 20, wherein, The barcode includes the barcode of the plate that holds the series of samples.

22. The system according to claim 20, wherein, The barcode includes encoded information.

23. The system according to claim 22, wherein, The encoded information includes the count of the samples in the series of samples.

24. The system according to claim 17 or claim 18, wherein, The one or more samples include the first sample or the first plurality of samples in the series of samples.

25. The system according to claim 17 or claim 18, wherein, The one or more samples include one or more samples from the series of samples, excluding the first or first few samples in the series of samples.

26. The system according to claim 17 or claim 18, wherein, The processor also performs the following operations: When the mass spectrometer detects the received peaks, it receives the peaks in the series of peaks in real time, and it receives the stored sample ejection time in real time when performing sample ejection and storing the ejection time. Real-time identification of one or more detected peaks with different characteristic values ​​or characteristic value patterns generated by the identifiable jet, from the received peaks. The delay time is calculated in real time based on the time of the identifiable injection and the time of one or more detected peaks. The mass spectrometer is instructed to recalculate the values ​​of one or more experimental parameters of the mass analysis using the delay time.

27. The system of claim 26, wherein the one or more experimental parameters include retention time or collision energy.

28. The system according to claim 17 or claim 18, in, The ADE device also performs an additional set of identifiable sprays on the last or subsequent samples in the series of samples. The processor further identifies an additional set of one or more detected peaks with different characteristic values ​​or characteristic patterns generated by the additional set of identifiable jets, and The processor also uses the time of the additional set of one or more detected peaks to identify the end of the series of samples.

29. The system according to claim 17 or claim 18, wherein, The processor uses templates with different feature value patterns to identify one or more detected peaks in the received peaks that have the different feature value patterns.

30. A method for aligning a sample with peaks detected in acoustic jet mass spectrometry (AEMS), comprising: An acoustic droplet ejection ADE device is used to perform a recognizable ejection on one or more samples in a series of samples using one or more ADE parameters that are different from other ejections performed on other samples in the series of samples, to produce one or more mass peaks with one or more peak characteristics that are different from the mass peaks produced for other samples, and to store the sample ejection time. The identifiable jet and other jets are received at the inlet of the tube using an open port interface, the received jets are mixed with the solvent in the tube to form a series of analyte-solvent diluents, and the series of diluents are delivered to the outlet of the tube. An ion source device is used to receive and ionize the series of diluents, thereby generating an ion beam; The ion beam is received using a mass spectrometer and its mass is analyzed over time to generate a series of detected mass peaks with intensity over time. The processor receives the peaks from a series of peaks and the stored sample ejection times; The processor is used to identify one or more detected peaks among the received peaks that are generated by the identifiable jet and have different characteristic values ​​or characteristic value patterns. The processor calculates the delay time based on the time of the identifiable injection and the time of one or more detected peaks. and The processor is used to align a series of detected peaks with the series of samples, using the delay time, the storage time, and the order of the series of samples.

31. A computer program product comprising a non-transitory and tangible computer-readable storage medium, the contents of the computer-readable storage medium including a program having instructions that are executed on a processor to perform a method for aligning a sample with peaks detected in acoustic jet mass spectrometry (AEMS), the method comprising: A system is provided, wherein the system includes one or more different software modules, and wherein the different software modules include a control module and an analysis module; The control module is used to instruct the acoustic droplet ejection ADE device to perform identifiable ejection on one or more samples in the series of samples using one or more ADE parameters with values ​​or value patterns different from those performed on other samples in the series of samples, to generate one or more mass peaks with characteristic values ​​or characteristic value patterns different from those generated on other samples, and to store the sample ejection time. The control module is used to instruct the open port interface to receive the identifiable jet and the other jets at the inlet of the tube, mix the received jets with the solvent in the tube to form a series of analyte-solvent diluents, and deliver the series of diluents to the outlet of the tube; The control module is used to instruct the ion source device to receive and ionize the series of diluents, thereby generating an ion beam; The control module is used to instruct the mass spectrometer to receive the ion beam and perform mass analysis on the ion beam over time, thereby generating a series of detected mass peaks with intensity over time. The analysis module is used to receive the peaks from a series of peaks and the stored sample ejection times; The analysis module is used to identify one or more detected peaks among the received peaks that are generated by the identifiable jet and have different characteristic values ​​or characteristic value patterns. The analysis module is used to calculate the delay time based on the time of the identifiable injection and the time of one or more detected peaks. and The analysis module is used to align a series of detected peaks with the series of samples using the delay time, storage time, and the order of the series of samples.

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