Method for determining a measure of decay rate and mass spectrometry system

Abstract

A method for determining a measure of a decay rate of an ion sample undergoing mass analysis in a mass analyzer using image current detection, the method comprising: receiving a detection signal of the ion sample from a transient detection of the ion sample obtained using the mass analyzer, the detection signal of the ion sample having a decay rate over time; and determining the measure of the decay rate of the ion sample based on an extrapolated resolution of the ion sample, the extrapolated resolution being an expected resolution of the detection signal under a condition that the decay rate over time of the detection signal of the ion sample is dominated by collision effects.

Description

Technical Field

[0001] This disclosure relates to methods and mass spectrometry systems for determining a measure of decay rate. Background Technology

[0002] Measurements of the collision cross section (CCS) area can provide valuable information about the structure of molecules such as proteins and protein complexes. It is known that in Fourier transform ion cyclotron resonance (FTICR) mass spectrometry, the ion-molecule collision frequency is related to the transient decay rate of the signal and can be measured by analyzing these rates (Parisod, G.; Comisarow, MB, *B. Chem. Phys. Lett.* 1979, 62, 303-305; Guan, S.; Li, G.-Z.; Marshall, AG, *Int. J. Mass Spectrom. Ion Processes* 1997, 167, 185-193). The collision frequency can be obtained by measuring the signal decay rate from the peak width, and thus the collision CCS.

[0003] This effect has recently been increasingly used to measure the CCS of both small molecules, known as CRAFTI (cross-sectional area through FTICR) (“Collision Cross Sectional Areas from Analysis of Fourier Transform Ion Cyclotron Resonance Line Width: A New Method for Characterizing Molecular Structure”, *Analytical Chemistry*, 2012, 84, 4851-4857) and proteins (Marshall et al., *Physical Chemistry and Chemical Physics*, 2016, 18, 713-717). It has also been used for orbital trapping (e.g., the Orbitrap manufactured by Thermo Fisher Scientific). TM(Analyzer) Mass spectrometry (Sanders JD et al., Analytical Chemistry, 2018; 90(9):5896-902). Following Guo et al. (Physical Chemistry and Chemical Physics, 2015, 17, 9060), it can be inferred that the signal attenuation in the Orbitrap analyzer is described by a high-energy hard-sphere collision model, in which each collision causes the ions to fragment and remove them from the detected ion pack.

[0004] In Fourier transform mass spectrometry (FTMS), the time-domain transient is theoretically approximated as sinusoidal if collisions are neglected, but in practice it is more complex. The time-domain signal in FTMS is typically approximated as a sine wave with an exponentially decaying amplitude, where the decay is primarily attributed to collisions with the background gas. Therefore, the decay constant is related to the CCS, as ions with higher CCS are expected to collide with the background gas more frequently, and thus the image signal provided by these ions is expected to decay more quickly. Generally, given two ions with the same mass-to-charge ratio (m / z), the ion with the larger mass (and therefore the higher charge) tends to have a larger CCS because it is expected to be physically larger to have such a large mass, and therefore will be expected to decay more frequently.

[0005] Wobschall et al. (Physical Review, 131, 1565 (1963)) described how ionic cyclotron resonance absorption lines in weakly ionized gases can be interpreted as yielding the mass-to-charge ratio and number of ions, as well as their collision frequencies. Based on the observed linewidths, they found that the collision frequencies of several ions are functions of pressure and electric field strength. These data were used to determine the ion-molecule collision cross section. Wobschall et al. (Journal of Chemical Physics, 47, 4091 (1967)) described using ionic cyclotron resonances to determine the CCS of hydrogen and other ions by defining the width of the ionic cyclotron resonance lines as a function of pressure and electric field strength.

[0006] In all FTMS instruments, the collision cross-section is measured relative to known ions, such as calibrator ions. However, these measurements indicate a significant deviation between the decay time of the separated ion clusters (e.g., specific charge states of proteins) and a wide mass range of clusters. Furthermore, no method has been demonstrated that is compatible with separation techniques such as liquid chromatography (LC) or gas chromatography (GC) on a timescale.

[0007] Existing methods typically rely on isolating the specific ion of interest to obtain sufficiently high intensities to yield reliable peak widths and thus determine the decay rate. Therefore, existing methods do not allow for online determination of CCS over a wide mass range, nor do they allow for the simultaneous parallel determination of CCS and m / z. Summary of the Invention

[0008] In view of this background and according to the first aspect, a method for determining the measure of the decay rate of an ion sample is provided. According to the second aspect, a method for determining the measure of the decay rate of an ion sample is provided. A computer program, a computer-readable medium, and a mass spectrometry system are also provided. According to the third aspect, a mass spectrometry system is provided.

[0009] This disclosure provides methods and apparatus for determining attenuation constants and cross-sectional area measurements in parallel with mass measurements and attenuation time correction. Specifically, this disclosure relates to methods and apparatus for performing Fourier transform mass spectrometry (FTMS). This disclosure recognizes that existing methods for determining CCS typically rely on separating specific ions for analysis to obtain sufficient intensity for reliable peak width determination. This disclosure recognizes that lower intensities lead to larger defocusing effects (e.g., due to space charge) and therefore result in less reliable signal attenuation / CCS measurements. Therefore, this practically does not allow for determining the attenuation constant / CCS based on analysis of lower ion intensities (such as those encountered over a wide ion mass range), and thus does not allow for actual or conventional CCS determination in parallel with conventional m / z determination.

[0010] To address the limitations of existing solutions outlined above, embodiments of this disclosure use signal strength metrics, such as signal-to-noise ratio (SNR), to correct for intensity-related factors (e.g., SNR and / or m / z correlation) of decay times, which correspond to CCS. In some embodiments, signal resolution measurements are extrapolated from low SNR values ​​to equivalent resolutions with higher SNRs. Measurements may be inaccurate at low SNRs, while at higher SNRs, the self-bundling of ions (which leads to dephase reduction) can be utilized to improve the determinism of the measurements. In some embodiments, an ion sample is generated following a separation technique, such as liquid chromatography (LC) or gas chromatography (GC), which, according to the LC or GC, has an elution spectrum over time. This disclosure also recognizes that recording the peak width of each analyte across the entire elution spectrum can provide more information about the decay constant and CCS and can be used to improve the statistics of CCS measurements. For example, tracking the peak width of each analyte across the entire elution spectrum can reduce the error in CCS determination after applying correction.

[0011] In some embodiments, the signal-to-noise ratio (SNR) of the mass peak (which depends on the number (intensity) of the ions corresponding to the peak) is corrected to improve the measured signal decay time and thus the accuracy of CCS determination. This disclosure further provides correction for m / z dependence. Therefore, the method uses the previously determined dependence of the decay constant on the calibrated characteristics (e.g., ion intensity (SNR), m / z). Thus, embodiments of this disclosure allow for the direct extraction of CCS values ​​from high-resolution, accurate mass spectra of ions over a wide mass range, preferably 'full MS' spectra. Such methods are fully compatible with high dynamic range scanning methods.

[0012] In some embodiments, the peak width of each analyte in the analyte entry elution spectrum can be tracked, and the final decay constant of the analyte of interest can be calculated as a weighted average of all points over the entire retention time, where lower intensity components receive significantly lower weights than higher intensity components. The decay constant can also be determined in this weighted manner based on all identified isotopic / charge states of the analyte.

[0013] This disclosure also provides improved hardware for performing such methods. The attenuation constant depends on the gas pressure in the mass analyzer. A practical and safe device is also provided for changing the gas pressure by leaking gas from a vacuum region of the mass spectrometer into the region where the mass analyzer is located. This enables a simpler and fail-safe design for gas leakage, preventing unacceptable pressure increases in the FTMS even in the event of a malfunction or human error.

[0014] Therefore, this disclosure generally provides a method for performing mass spectrometry, wherein the attenuation constant, m / z, and calibration are performed online. Such a method may include generating an ion stream, such as from an ion source, and implanting a collection of ions from this stream into a trapped ion optical device, such as a mass analyzer, in which the ions perform periodic motions constrained by an electromagnetic field. An image current is detected of the periodic motion of the ions over a time period during which at least a portion of the ions collide with gas molecules in the trap. Characteristics of the periodic motion of the ions, such as intensity, phase, frequency (i.e., m / z), and attenuation constant, one or more of these can be determined simultaneously for multiple ion species within the ion collection. The value of the attenuation constant or CCS for each species can be determined based on a dependence on prior calibration of the ion characteristics. The dependence on prior calibration may include any one or more of the following: the intensity of the ion species of interest; the intensity and / or frequency of the ion species of interest; and / or the intensity and / or frequency distribution of all ion species containing the ion species of interest. Compared with existing methods, improvements can be achieved in the dynamic range, accuracy, and precision of CCS measurement results, and signal attenuation can be used for quality control of detected quality peaks.

[0015] These and other advantages will become apparent from the following description of preferred embodiments. Attached Figure Description

[0016] The present disclosure will now be described by way of example with reference to the accompanying drawings, in which:

[0017] Figure 1A and 1B The relationship between the decay constant, the number of ions in the packet, and the elution time is shown.

[0018] Figure 2A A method for determining the decay rate of an ion sample according to a first embodiment is shown;

[0019] Figure 2B A method for determining the decay rate of an ion sample according to a second embodiment is shown;

[0020] Figure 3 Data suitable for implementing the first and second embodiments is shown; Figure 4A Showing the target Figure 3 The resolution of the peak intensity of the data;

[0021] Figure 4B It shows Figure 4A Data regarding resolution in relation to signal-to-noise ratio;

[0022] Figure 5 The observed resolution and SNR values ​​are shown, along with the fitting that can be used to obtain the extrapolated resolution.

[0023] Figure 6 A mass spectrometry system according to a third embodiment is shown;

[0024] Figure 7 The effect of pressure on the attenuation constant is shown;

[0025] Figure 8 The effect of pressure on resolution is shown; and

[0026] Figure 9 It shows Figure 8 The summary of data. Detailed Implementation

[0027] Based on theoretical and experimental examinations of signal attenuation in FTMS (and especially Orbitrap MS), it has been recognized that ions undergo numerous space charge-related effects. The most notable appears to be the so-called "self-bundling," where the "natural" broadening of the ion pack is suppressed at high ion populations due to the combined effects of space charge and electric field nonlinearity, as described in US-7,714,283. By fabricating highly accurate Orbitrap analyzers and optimizing their tuning, these effects can be neglected or at least reduced to tolerable levels in many cases. However, when CCS is calculated based on the attenuation constant, space charge effects (e.g., self-bundling) can still be quite apparent, such as... Figure 1A As shown. In FTMS, the attenuation constant can be determined based on the width of the mass peak in the mass spectrum obtained from the transient, for example using a Fourier transform with apodization and zero filling known in the art. The general equation for determining the attenuation constant from Fourier transform mass spectrometry data is presented in the "Theory and methods" section of Marshall et al., Physical Chemistry, Chemical Physics, 2016, 18, 713. Similarly, the method from Sanders JD et al., Analytical Chemistry, 2018; 90(9): 5896-902 can also be used. The error determined by CCS depends on the parameters of the detected mass peak, mainly the SNR, where lower intensity peaks experience stronger space charge and other defocusing effects.

[0028] Although it is difficult to determine the actual number of ions in the packet, the number is proportional to the SNR of the peak for a given transient duration and decay constant, where the coefficient of the proportion depends only on the thermal noise of the detector's preamplifier and its frequency dependence. The relationship between SNR and ion number is described, for example, in Section 2.1 of Eiler et al. (Analysis of molecular isotopic structures at high precision and accuracy by Orbitrap mass spectrometry) (International Journal of Mass Spectrometry, Vol. 422, 2017, pp. 126-142, ISSN 1387-3806), which is incorporated herein by reference. The relationship described by Eiler et al. for determining ion number can be used in the embodiments of this disclosure when the signal intensity or SNR is described as being used.

[0029] Figure 1AThe dependence of the attenuation constant on the number of ions with different m / z ratios in the pack is shown. Error bands caused by statistics and potential thermal noise from the preamplifier are shown as gray bands. Figure 1A The hash band on the left shows the lower limit of detection. It can be seen that at low ion counts, the measured attenuation constant (and therefore the collision cross section) is systematically higher than that of the same sample analyzed with higher ion counts. Sometimes it is desirable to measure the collision cross section to characterize molecules, as the collision cross section is an inherent feature of molecules. Therefore, this disclosure seeks to provide a method that takes into account... Figure 1A The changes shown are accurate measurements of the attenuation constant and / or collision cross section.

[0030] Figure 1A The dependence can be obtained first using a calibration mixture of compounds (also described as a calibrator), and then refined for a specific sample or experiment. While the decay constant depends heavily on m / z and / or charge state, Figure 1A The shape of the curve depends primarily on the number of ions in the packet and to a lesser extent on the m / z. However, second-order effects can also occur, especially when very strong peaks appear near the ion of interest. FT data processing methods (e.g., amplitude, absorption, enhanced FT (eFT), etc.) can also affect the determined values, as each method may exhibit its own dependence of peak width on the attenuation constant and intensity. However, this dependence is not necessarily problematic if the same FT processing method is used for calibration and subsequent analysis. Any FT method can be used as long as the same method and appropriate statistics are applied to both the calibrator and the sample.

[0031] The dependence shown in Figure 1 can be used for the elution spectra of each mass peak and charge state across each isotope of the analyte of interest, such as... Figure 1B As shown, the attenuation constant measurement results are corrected after acquisition. Figure 1B The black circles in the diagram represent the time points at which the elution spectrum across the mass peaks was used to extract the measurement results. It can be seen that these time points on the elution spectrum correspond to different decay constants. The allocation of isotopes and charge states can be performed using an algorithm similar to that described in US-10,593,530, which is incorporated herein by reference. The final decay constant of the analyte of interest can be calculated as a weighted average of all points and / or all isotopes across the retention time, where lower intensity components receive higher corrections and significantly lower weights compared to higher intensity components. It may be preferable not to include all isotopic peaks, but only the most intense peaks, e.g., exceeding 30% or 50% of the most intense peaks in the cluster. Alternatively, only points with peak intensities greater than a certain percentage (e.g., 10%, 20%, 30%, 40%, etc.) can be used. In any case, Figure 1BIt is shown that, for each m / z ratio, the measured decay time at a given time point on the elution spectrum can be corrected.

[0032] For example, considering the first elution peak at m / z1, when the number of ions in the bag is relatively low, the first measurement of the attenuation constant will be obtained (i.e., Figure 1B (The bottom black circle). This causes... Figure 1A The left side of the graph measures the attenuation constant, which leads to a large error in the measurement result. As time progresses, the next two black circles (i.e....) Figure 1B The second and third (bottom black circles) show that the measurement results of the attenuation constant were extracted for a relatively large number of ions in the package, which means that the attenuation constant was obtained from... Figure 1A The measurements were taken on the right side of the curve, thus making the measurement error relatively small. Then, the fourth, bottommost black circle originates from the tail edge of the retained peak, and again produces [data from...]. Figure 1A The decay constant is measured on the left side of the elution spectrum. Elution at m / z² is repeated in a similar pattern. Therefore, different measurements extracted at different points in the elution spectrum can be corrected, and / or the measurements can be weighted in determining the average decay constant of a given sample. Preferably, the different measurements extracted at different points in the elution spectrum are corrected and weighted: first, the data are corrected using data from calibrator measurements, and then a weighted average is obtained for better statistical analysis.

[0033] The measured attenuation constant or CCS value can be corrected based on m / z. For example, it can be... Figure 1B As observed, different m / z values ​​result in different decay constant curves for ion counts. m / z-based correction can be implicit because m / z indirectly affects the decay rate: for a given charge state, higher m / z values ​​tend to have higher CCS. Furthermore, for a given transient length, higher m / z values ​​have lower resolution due to lower frequency oscillations. Therefore, these two m / z-related effects become complex when correcting for measures of the decay rate (e.g., decay constant or CCS) of the ion sample by adjusting intensity measures (e.g., SNR). In principle, more refined corrections can be developed using machine learning based on large datasets collected from large datasets. These datasets could cover specific chemical categories, such as trypsin peptides, lipids, glycans, etc., and / or utilize mass spectrometry similarities.

[0034] from Figure 1BIt is evident that, due to the larger error in determining the attenuation constant for lower intensities, the error in the attenuation constant of peak m / z2, and therefore the CCS error, will be significantly greater than the error of m / z1. To improve SNR and thus reduce CCS error, high dynamic range scanning is preferably used, as disclosed in US-10,224,193-B2 and WO-2018-134,346-A1, both of which are incorporated herein by reference in their entirety.

[0035] Figure 1A and 1B This demonstrates the limitation on resolution in FTMS signals imposed solely by the vacuum conditions in the detector on the ion species. As the number of oscillating ions in a given packet increases, virtually all spatial / image charge-related signal coherence loss paths tend to shrink, causing the observed resolution to gradually increase until a point (known as self-bundling). At this point, the detection signal of the ion sample typically exhibits an exponential decay pattern dominated by collisional effects. At this point, the only decay mechanism is through collisions between ions and background gas molecules. This is caused by… Figure 1A The platform on the right side of the middle and Figure 1B The upper panel is shown on the right side. Some embodiments of this disclosure seek to ensure that the resolution values ​​used for attenuation constant or CCS determination come from those "platform" regions.

[0036] Figure 2A A method, described in general language, for determining a measure of the decay rate of an ion sample undergoing mass analysis in a mass analyzer, according to a first embodiment of this disclosure, is shown. The method can be used with... Figure 1A and 1BThe data shown determines a calibration measure of the decay rate of the ion sample. The method includes a first step 201 of receiving a detection signal of the ion sample from a transient detection obtained using a mass analyzer, the detection signal of the ion sample having a decay rate over time. This detection signal may be an image current detected by the mass analyzer. In a second step 202, the method includes determining an adjustment function for the ion sample based on (e.g., including, depending on) the following: a measure of the intensity of the detection signal of the ion sample (e.g., SNR or total ion count) and / or a measure of the mass-to-charge ratio (e.g., frequency); and a measure of the intensity of the detection signal (e.g., SNR or total ion count) and / or a measure of the mass-to-charge ratio (e.g., frequency) of the detection signal previously obtained by the mass analyzer for a calibrator. The method includes a third step 203 of determining a measure of the decay rate of the ion sample by adjusting the measure of the decay rate of the detection signal of the ion sample over time using the adjustment function. In this way, an accurate measure of the decay rate of the ion sample can be obtained because the intensity and / or mass-to-charge ratio of the signal from the calibrator (e.g., with an accurately known decay constant and / or cross-section) are used to determine the adjustment function used to adjust the measured value of the ion sample. Therefore, it is possible to consider... Figure 1A and 1B The attenuation constant or CCS dependency shown.

[0037] Alternatively, a weighted average can be calculated. For example, a method can be provided for determining a weighted measure of the decay rate of an ion sample being mass-analyzed in a mass analyzer, the method comprising: receiving multiple detection signals of the ion sample from transient detections obtained using the mass analyzer, the detection signals of the ion sample having a decay rate over time; determining multiple measures of the decay rate of the ion sample; determining the weighted measure of the decay rate of the ion sample by taking a weighted average of the multiple measures of the decay rate of the ion sample (and optionally correcting those measures of the decay rate), wherein relatively high intensity measures of the detection signals of the ion sample are weighted to provide a greater contribution to the weighted average compared to relatively low intensity measures of the detection signals of the ion sample. The multiple detection signals of the ion sample can be obtained at multiple time points spanning the elution spectrum of the ion sample. This is consistent with... Figure 2A The process shown is similar, and the various steps described in this disclosure can be equally applied to this alternative aspect. However, this aspect recognizes that a more accurate measurement can be made by taking a weighted average of multiple measures of the decay rate of the ion sample. The weighted average may completely exclude certain measures of the decay rate (e.g., because the resolution of said measures is extremely poor), and therefore it may not be necessary to correct for those values ​​when calculating the weighted average (because the contribution of those values ​​would be zero).

[0038] The method disclosed herein may include determining a weighted measure of the decay rate of an ion sample by taking a weighted average of multiple measures of the decay rate of the ion sample. For example, any measure that describes the decay rate of the ion sample can be a weighted measure. This ensures that measures of the decay rate of the ion sample that are statistically likely to be accurate are given priority, thereby improving the accuracy with which the decay constant and CCS can be determined.

[0039] In such methods, multiple measures of the decay rate of the ion sample can be correlated with one or more relatively high intensity measures of the detection signal of the ion sample (e.g., Figure 1A and 1B The value on the right) and one or more relatively low intensity measures of the detection signal of the ion sample (e.g., the value on the right) and the detection signal of the ion sample. Figure 1A and 1B The values ​​on the left correspond to the values ​​on the right; and one or more relatively high intensity measures of the detection signal of the ion sample are weighted to provide a larger contribution to the weighted average compared to one or more relatively low intensity measures of the detection signal of the ion sample. In this way, a smaller contribution to the overall average is made by values ​​extracted with relatively low ion counts and therefore low accuracy. In some cases, the weighted average may exclude one or more measures of the decay rate of the ion sample for which the intensity measure of the detection signal of the ion sample is below a threshold. For example, if these values ​​are known to lead to erroneous results, it may be desirable to ignore any values ​​extracted with particularly low ion counts.

[0040] In the context described herein and continuing to use the previously used general language, the measure of the decay rate of an ion sample can be either the decay constant or the collision cross section. Since the CCS can be determined from the decay constant (and vice versa), any measure of the decay rate of the ion sample can be used in the algorithms of this disclosure.

[0041] As previously mentioned, the actual number of ions in the packet may be difficult to determine, but it is proportional to the SNR of the peak for a given transient duration and decay constant. Therefore, in the previously used general language, determining the adjustment function (e.g., scaling factor) for the ion sample can be based on the ratio between an intensity measure of the detection signal of the ion sample and an intensity measure of the detection signal previously obtained for the calibrator. For example, under certain conditions, Figure 1A and 1B The curves in the two measurements can have essentially the same form, but are approximately correlated by a proportionality constant. Therefore, this relationship can be used to correct for measurements of ion sample extraction. Taking the ratio between the two measurements reduces the need to account for various complex factors.

[0042] As a hypothetical example, consider measurements extracted from an ion sample in a package having, for example, 100 ions (or equivalent SNR). This sample can provide an orientation towards Figure 1A and 1B The data points on the left (i.e., close to the detection limit) may lead to any overestimation of the decay constant or CCS due to space charge or other effects. However, it is known from experiments on calibrators (which, of course, have known composition and known decay constant and CCS) that an ion pack with 100 calibrator ions causes the decay constant to be overestimated by 10%. Therefore, the decay constant of an ion sample can be determined using data points from a pack with only 100 ions, and the decay constant can be made more accurate by reducing the calculated decay constant by 10%. It will be understood that a similar approach can be applied to CCS calculations. Therefore, in general, this disclosure provides an adjustment function for an ion sample that indicates the amount by which the decay rate of the detection signal of the ion sample over time is adjusted to compensate for the error when measuring the decay rate of the detection signal of the ion sample over time. The adjustment function may define an offset (e.g., an offset of the measured value may be added to or subtracted from it) or provide a scaling factor indicating a percentage of error. In this context, the measurement of the decay rate of the detection signal of the ion sample over time using an adjustment function can include scaling the measurement of the decay rate of the detection signal of the ion sample over time by a scaling factor. The adjustment function described herein can be any procedure that receives a mass spectrometry signal and outputs a corrected CCS and / or decay constant by comparing the mass spectrometry data against the mass spectrometry data of a calibrator. Therefore, a more accurate measurement of the decay rate of the ion sample can be obtained.

[0043] For example, multivariable functions can be restricted. The output of the multivariable function is a corrected decay constant. This function τ 校正 The following inputs are taken: the uncorrected attenuation constant τ0 determined from the mass spectrometry data; the signal-to-noise ratio (SNR) of the mass spectrometry data; and the mass-to-charge ratio (m / z) expressed from the mass spectrometry data. It can also use a set of other inputs X, such as the total SNR of the entire spectrum, characteristics of the most recent or most intense mass peak, etc. Therefore, X can be considered as an optional variable that can be omitted.

[0044] function τ 校正 The form can be determined for calibrators with known compositions. Since calibrators have known compositions containing various known component species, the range of corrected m / z values ​​for the calibrators is known. Furthermore, a series of correction attenuation constants (i.e., functions τ) are also known. 校正 The corrected output will be known as a good calibrator. Therefore, the function τ for a specific experimental setup 校正The form can be determined by solving an optimization problem using data obtained from the calibrators. Therefore, when embodiments of this disclosure perform the step of determining the adjustment function for the ion sample, this may mean calling function τ. 校正 If determined using calibrators.

[0045] What will be understood is that τ can be used. 校正 Other inputs. For example, the function τ 校正 The ion count in the packet can be used as input instead of the SNR, and the frequency of the mass analyzer's detection signal can be used as input instead of m / z. These are simply equivalent to coordinate transformations. Furthermore, τ can be omitted. 校正 Some of the inputs are from the standard input. For example, in the case of a desired full MS scan, it might be preferable to perform calibration based on both SNR and m / z (or frequency), but for a single scan, calibration based solely on SNR (or any other intensity metric) might be sufficient. For m / z-based calibration, a calibrator mixture can be used, comprising multiple calibration ions of different m / z (preferably over a wide range), such that a relationship of ions to Figure 1 is obtained for each m / z, and then the derived adjustment value for each number of ions can also vary with m / z, so that a separate curve of adjustment value versus m / z for each number of ions can be obtained and used for calibration. Ideally, a mixture of as many calibrators as possible should be used for calibration. For example, the mixture could be FlexMix for instrument calibration, or alternatively, a mixture of peptides produced by digesting bovine serum albumin (a standard quality control sample in proteomics), etc. Spline interpolation can then be used, for example, between the calibrated peaks.

[0046] In any case, as defined above for the function τ 校正 The output is provided as a corrected attenuation constant. Of course, the substitution function can be limited and falls within the scope of this disclosure, such as:

[0047] τ 偏移量 ≡τ 校正 (τ0;SNR;m / z)-τ0

[0048] τ 缩放 ≡τ 校正 (τ0;SNR;m / z) / τ0

[0049] τ 偏移量 The output will be the amount needed to add to the uncorrected attenuation constant to provide the corrected value. Similarly, τ 缩放 The output will be a scaling factor, and the uncorrected attenuation constant will need to be scaled by this scaling factor to provide a corrected value. It will also be understood that the function τ... 校正It can be represented by the equivalent function σ 校正 Instead, the equivalent function receives the same input and provides a corrected CCS value (or offset / scaling factor) as its output.

[0050] Another method for calculating the accurate decay constant or CCS value is as follows. For the calibrator, a curve similar to the one in Figure 1 can be obtained (i.e., there exists a series of decay constant measures or CCS for ion quantity, S / N, or intensity, etc.). Interpolation between points can be used, or a fitting function can be used to approximate the curve. Then, from the curve, an adjustment value for each ion quantity, S / N, or intensity can be found (based on the deviation from the "known" decay constant). Finally, the decay constant or CCS of the "ion sample" can be corrected by using an adjustment value (from the calibrator curve) corresponding to the same ion quantity, S / N, or intensity as the ion sample.

[0051] Throughout this disclosure, the intensity measure of the detection signal for an ion sample may include any one or more of the following: total ion count; signal amplitude; and / or signal-to-noise ratio. Furthermore, the intensity measure of the detection signal previously obtained for a calibrator may include any one or more of the following: total ion count; signal amplitude; and / or signal-to-noise ratio. The mass-to-charge ratio measure of the detection signal for an ion sample may include frequency (or equivalently, the time period of the signal); and / or the mass-to-charge ratio measure of the detection signal previously obtained for a calibrator may include frequency (or equivalently, the time period of the signal).

[0052] Next turn Figure 2B The method according to the second embodiment is shown. Figure 2B The method is similar to the 2A method in some respects. Figure 2B The method is a measure of the decay rate of an ion sample being mass-analyzed in a mass analyzer using image current detection. The method includes a first step 211 of receiving a detection signal of the ion sample from a transient detection obtained using the mass analyzer, the detection signal of the ion sample having a decay rate over time. This can be compared with... Figure 2A Step 201 is essentially the same. The method may further include an optional second step 212, which determines whether the resolution of the detection signal of the ion sample indicates that the decay rate of the detection signal over time is dominated by collisional effects (e.g., self-splitting). This can be achieved by considering, for example, whether the resolution of the mass spectrometry detection signal is within a certain range. Figure 1A and 1B To obtain it from a stable platform.

[0053] Whether self-bundling occurs is not necessarily important, but it does affect which corrections are used. Therefore, step 212 can be omitted, or it can be used instead for quality control. For example, step 212 may include determining any one or more of the following: whether the peak is baseline resolved (i.e., whether the peak reaches the baseline on both sides without interfering with other peaks); whether the SNR is high enough to even consider the peak; whether the peak belongs to an isotopic cluster; and then whether the peak will be included in the weighted average.

[0054] Finally, the method includes a third step 213 to determine a measure of the decay rate of the ion sample. If the resolution of the detection signal of the ion sample indicates that the decay rate of the detection signal over time is dominated by collision effects, then the measure of the decay rate of the ion sample is determined based on the decay rate of the detection signal over time. For example, if the data comes from a stable plateau of values, it may not be necessary to correct the decay constant or CCS measurement results, and the CCS or decay constant of the ion sample can be calculated using the decay constant of the signal. On the other hand, if the SNR of the detection signal of the ion sample indicates that the decay rate of the detection signal over time is not dominated by collision effects, then the measure of the decay rate of the ion sample is determined based on the extrapolated resolution of the ion sample. Under the condition that the decay rate of the detection signal over time is dominated by collision effects, the extrapolated resolution is the expected resolution of the detection signal. Therefore, if the value is taken from... Figure 1A , 1B To the left of 3(III), the resolution can be determined by extrapolating to the region where the condition is collision-dominated and therefore more accurate. Thus, this disclosure provides a method that can automatically improve the accuracy of attenuation constants and / or CCS measurements.

[0055] In this disclosure, "dominated" means that the decay rate of the detected signal can be fitted to a first-order exponential decay curve to a degree exceeding a minimum accuracy threshold. This minimum threshold can be, for example, a user-set or factory-set / defined threshold (e.g., a minimum threshold can be programmed into the hardware during manufacturing) and represents the point at which the transient decay rate changes from exponential to acceptable, and then to no longer acceptable exponential, such that the fitting method described herein fails to work. It should be understood that, in this respect, there is no explicitly defined cutoff point in the transition from exponential to non-exponential decay. In some cases, a graph of resolution versus SNR may show an inflection point (e.g., where the resolution begins to flatten after a continuous rise), and this inflection point can also be considered a threshold above which the condition is considered collision-dominated. Alternatively, a condition can be considered "collision-dominated" when the resolution (or other equivalent measurement) reaches a certain percentage (e.g., 80%, 90%, 95%, or 99%) of its value in a stable plateau region.

[0056] Figure 3 The LC elution spectrum (I) of the charge state Z = 3+ isotopic envelope of the compound with a single isotopic weight of 2200.09 Da (II) is shown. The isotopic resolution values ​​are distributed across the elution spectrum in logarithmic order. 10 The scale is plotted as a function of the signal-to-noise ratio (III). In a general sense, multiple measures of the decay rate of the ion sample can be determined for multiple retention times in the elution spectrum.

[0057] Such data can be used to ensure that measurements are extracted from the region where the information is most reliable (i.e., preferably near or in the self-clustering region). While high-intensity peaks located in the self-clustering region are desirable, mass spectra typically exhibit a log-normal distribution of intensity, resulting in low abundance for most peaks. For LC (or GC) experiments, some eluted samples have very low abundance, making it impossible to obtain measurements from a stable platform.

[0058] LC spectrum, or in Figure 3 In case (I), ion monitoring (SIM) can be used as a measure of the number of ions in each ion pack. Therefore, the initial steps may include identifying high ion count "plateau" levels (e.g., Figure 1B The value of the decay parameter in the stable region (within the range). Since resolution and decay are closely related (i.e. proportional in the case of collision-only schemes), for the pure collision component of the decay constant, the strategy is the same when the decay parameter is known in writing, or the strategy uses resolution as an intermediary.

[0059] For CCS analysis, it is not necessary to limit the analysis to a single m / z species for each compound. Since all isotopes within a given cluster have exactly the same size (and differ only in their mass), it can also be beneficial to use resolution data across the entire isotopic envelope. Therefore, the term "ionic species" can be generalized to all isotopes of a given charge state of a given compound. Figure 3 (II) shows seven peaks spaced apart at 0.33 m / z, indicating isotopic variants of triple-charged ions. Therefore, in general, in the methods described herein, multiple measures of the decay rate of an ion sample can be determined for a variety of different isotopic compositions. Thus, the weighted average described herein can be based on measures of the decay rate of multiple isotopic variants of an ion sample. This allows for the analysis of multiple isotopic variants of a single analyte, which can improve error statistics.

[0060] Since higher intensity peaks tend to provide a more accurate estimate of the resolution value, it may be beneficial to use only the values ​​near or at the apex of the SIM peak (i.e., near the plateau) to calculate the attenuation constant. However, this is not necessary in all embodiments. For example, as referenced... Figure 5In more detail, some embodiments of this disclosure use the following procedure to determine the attenuation constant. First, a set of data is obtained, such as... Figure 3 (III) A set of data. Then, the best-fit line was determined to attempt to establish a relationship between SNR and resolution. Figure 3 In (III), this best-fit line will flatten at a constant resolution of approximately R = 63000, above an SNR value of approximately 50. Then, when determining the attenuation constant or CCS measurement for a species with an SNR of 10 and corresponding R = 55000, it becomes apparent that this particular species did not undergo self-bundling, as R = 55000 is significantly lower than the plateau where self-bundling occurs. Therefore, a large error is expected for this species in terms of attenuation constant and CCS, since both can be directly calculated from R, and this measured value of R = 55000 indicates suboptimal experimental conditions. This large error in attenuation constant and CCS can be corrected by using R = 63000 instead of R = 55000 when determining the attenuation constant or CCS. This is because if a higher SNR could be obtained (e.g., by having a large amount of analyte and therefore more ions in the package), the resolution would be R = 63000. This best-fit line can be considered... Figure 3 All points in (III).

[0061] Alternatively, to improve statistics, a resolution-weighted average can be used for all observed peaks of a particular ion species, as follows:

[0062]

[0063] in It is a resolution-weighted value, R i C is the reported resolution value for each individual peak. i Is using from Figure 1A , 1B The calibration of 3(III) corrects for this value (C) i ≥1), I i It is a measure of the intensity of a single peak, and W(I) i The resolution value assigned to the peak is a weighted average of its intensity as a function of the peak's resolution value. The resolution weights for different ranges of SNR can be determined using a weighted average. For example, this can be achieved by... Figure 3 The trend line is obtained by using the rolling average of the data in (III). Alternatively, This can be a weighted resolution, where only peaks within the self-bundling region are weighted (i.e., peaks whose intensity is not high enough to indicate self-bundling are excluded). The intensity measure can be in any unit, such as the absolute value of the peak's apex in amplitude or absorption FT spectra, SNR, etc.i =1), which can be linear with respect to the weights (e.g., W(l)). i ) = constant * I i ), or may reflect Figure 1B Nonlinearity of curves with more complex functions (e.g., W(I)) i ) = constant * I i P (where p can be a constant). Other weighting strategies are also possible. In any case, by assigning lower weights to less intense peaks, a more accurate plot of SNR (or equivalent measure) against resolution can be obtained (this plot can be used to correct for attenuation constants and CCS) to prevent peaks with large errors from skewing the established trend line.

[0064] It is also possible to find parameters that accurately describe the curve and reliably extract the resolution value. For this strategy to work, a model describing the phenomenon is needed. A preferred choice for such a model is a function that flattens on the y-axis (here, representing the attenuation constant or resolution). The best example of a smooth function with this property is an exponential plateau:

[0065] Y = Y 平台 -K*e -γ*x (II)

[0066] Where Y 平台 The platform seeks values, and the coefficients K and γ describe the attainment of Y. 平台 The rate of increase of the previous function. It should be noted that this function does not need to be smooth. For the purposes of this disclosure, this function can be a piecewise function, for example...

[0067]

[0068] The coefficients a, b, and c describe the point x. 临界值 The function represents a parabolic ascent before reaching the platform. It can also be a piecewise linear function that approximates a smooth function. These functions are merely examples, and other functions may be used in embodiments of this disclosure.

[0069] The parameters of these functions can be obtained in a variety of different ways, including minimizing the difference between the observed values ​​and those predicted by the function. The optimization problem can be described in terms of the norm of minimizing said difference, for example, in the Lp space (when p = 2, this optimization procedure is called the least squares method). It is worth noting that it can be beneficial to consider other properties of the data in the optimization procedure (e.g., for lower intensity peaks, the distribution of values ​​tends to be higher, such as...). Figure 3 (as shown in (III)). For example, one could consider introducing weights in weighted least squares:

[0070]

[0071] Where β is the set of parameters to be sought, y(x i ;β) is a point x i The value of the model function at that location, - is point x i The observation results at the location, and w i Is with Associated weights. Weights can be functions of intensity or some statistical property (e.g., local σ of diffusion). Preprocessing the data before fitting by removing outliers or smoothing it using filters can also be beneficial. A good example of such preprocessing would be applying moving average filtering with different styles (e.g., exponential modifications) to different time periods depending on the local statistical topography of the data.

[0072] Regardless of the method used to extrapolate the resolution value, the relationship between resolution and attenuation constant needs to be utilized. Figure 1A , 1B and Figure 3 The platform shown in (III). Collision attenuation in FTMS typically follows an exponential law, i.e.

[0073] a(t) = a0cos(ω0t)*e -τt (V)

[0074] The intensity 'a' of the oscillation of the signal with frequency 'w0' exhibits an exponential trend, decreasing at a rate 'τ' over time 't' from its initial value 'a0'. After Fourier transform, the absorption mode spectrum exhibits a Lorentzian peak.

[0075]

[0076] It has a magnitude A0 at ω0 and a half maximum full width (FWHM) of 2τ.

[0077] Since equation (VI) is the result of the Fourier transform of equation (V) on an infinitely long signal, the peak width of 2τ (which can be used to determine the CCS) can be a good approximation of a rapidly decaying signal. In other cases, it may be beneficial to consider the finite duration of the FTMS transient signal.

[0078] One method for correction was proposed by Li et al. (Dayu Li, Yang Tang, and Wei Xu, Analyst, 2016, 141, 3554) using the following expression:

[0079]

[0080] Where T is the duration of the transient signal (known from the instrument settings), and Δω' is the observed spectral FWHM (i.e., the FWHM of the peak used to determine the attenuation constant). Equation (VII) can be solved numerically to determine a more accurate relationship between the peak width (i.e., FWHM in the frequency domain) and the attenuation constant, rather than a simple approximation of FWHM as 2τ of the Lorentz peak.

[0081] One way to determine whether the correction in equation (VII) is beneficial is to compare Δω' with the limitation imposed on resolution by the length of the time-domain signal. Any FTMS transient can be represented as a multiplication of an infinitely long oscillating signal with a square function of duration T, which in the frequency domain is transformed into the convolution of the FT image of the signal with the image of a windowed function, i.e.

[0082]

[0083] Therefore, it may be beneficial to use the correction equation (VII) when the FWHM of equation (VIII) is equivalent to Δω', while the benefit may be less obvious when Δω' is much larger, especially for noisy signals. In the previously used general terminology, the step of determining the measure of the decay rate of the detection signal of the ion sample over time is based on the peak width of the detection signal of the ion sample (e.g., the width of the peak in the frequency domain Δω that can be used to determine the decay constant). Preferably, the step of determining the measure of the decay rate of the detection signal of the ion sample over time takes into account (e.g., including some correction for errors caused by using a discrete Fourier transform on a signal of finite duration) the duration of transient detection of the ion sample. For example, a correction to the form of equation (VII) may be appropriate and advantageous.

[0084] Figure 4A Experimental data demonstrating the self-bundling effect are provided. Figure 4A In the diagram, the horizontal axis represents the total ion count of the peaks detected from the oscillating ion cloud. The Y-axis represents the observed value of the resolution for the selected peak. The resolution value is defined as... Where Δm is the FWHM of the peak at position m (in the mass domain). Figure 4A Intensities are reported in arbitrary units (AU), but may also be expressed in signal-to-noise ratio (SNR) or other units. Reported values ​​are taken from ion species at 739.03Th and charge state Z = 3+. Resolution increases with the number of ions until a plateau is reached, at which point the ions tend to be “self-bundled.” At this point, the ion cloud no longer “dephases,” and the only source of attenuation is the death of individual ions due to collisions with background gas molecules. Figure 4AThe data are results extracted from the same system under different pressure conditions by Orbitrap FTMS experiments: (I) low pressure, HCD gas valve closed; and (II) high pressure, gas on. Figure 4B In fact, it shows the relationship with Figure 4A The same diagram. Figure 4B In the middle, the resolution is relative to log. 10 (SNR) was plotted with the gas on / off. SNR is a preferred indicator for quantifying the number of ions in the packet, and Figure 4B The logarithmic plot is used to more clearly show the plateau in resolution reached as the ion count increases.

[0085] Figure 5 It provides ways to use data numerically, such as Figure 4A and 4B The data shown are examples of obtaining improved CCS estimates using embodiments of this disclosure. Figure 5 All data in the instances are from commercial OrbitrapExploris TM Collected on a mass spectrometer. The resolution was set to 120 kHz, corresponding to a transient length of T = 256 milliseconds. Equation (IX) provides the mass calibration parameters B and C in the relationship between mass and frequency (kHz):

[0086]

[0087] exist Figure 5 In the example, the values ​​are B = 169449512.441 and C = 72890453.4333.

[0088] As previously described, the initial steps in evaluating CCS involve determining the attenuation caused solely by collisions with residual gas. One approach is to assess the resolution from the onset of beamforming. Figure 5 This demonstrates how to fit the exponential plateau function, such as in equation (III), to the function derived from the L2 norm by minimizing the L2 norm. Figure 3 The observed distribution of resolution (III).

[0089] The resolution platform is located in Y 平台 =63070.3159, and achieved at an SNR level of approximately 50. Since resolution in the quality domain is defined as... Therefore, Δω' or Δf (FWHM of the frequency) can be obtained using equation (IX). Specifically, equation (IX) can be used to prove that equation (IX) is affected by B / f 2 High-frequency domination of term C / f 4The term Δω' is proportional to the following: frequency (478.840 kHz in this case); and resolution at the plateau, which is 63070.3159. In this particular case, Δf = 3.7961 Hz, which can be directly measured: the frequency FWHM of the resolution in the mass domain, from which the value of the frequency at half maximum of the peak can be calculated, i.e., for a resolution of 63070.32 at 739.0237 Da, the Δm / z at half maximum is 0.011717, and the mass itself is 739.0237 - 0.011717 / 2 = 739.0178 and 739.0237 + 0.011717 / 2 = 739.0296, where the corresponding frequencies (hereinafter according to equation (IX)) are 478838.7 and 478842.5 Hz, thus giving Δf = 3.796085. Since the mass resolution is close to the constraint imposed by the duration of the transient (in this case, approximately 80 kΩ in the mass domain, corresponding to Δf = 2.9907 Hz), t cannot be simply estimated using 2τ = Δω'. Instead, equation (VII) is used for a more accurate determination. Solving equation (VII) numerically yields the obtained value of the attenuation parameter τ = 0.3798 s. -1 .

[0090] Once the decay value is obtained, the CCS can be determined as described in Sanders JD et al. (Sanders JD et al., Analytical Chemistry 2018; 90(9):5896-902). The pressure reading on the UHV meter is used (for the data presented here, the pressure reading is 5.85 x 10⁻⁶). -10 The fact that mbar is approximately half of the residual vacuum in the Orbitrap analyzer allows us to obtain the following cross-section σ:

[0091]

[0092] Where P is the pressure inside the Orbitrap analyzer, L is the length of the ion flight path along the Z-axis during each oscillation (65.1 mm in this case), f is the axial frequency of the ion (478.840 kHz in this case), T is the temperature (295 K), and k is the Boltzmann constant. For this ion species, the obtained CCS value is... This is a reasonable cross-section for the triple-charged peptide within this mass range. Therefore, it can be seen that the method of this disclosure can be used to determine accurate CCS values. Specifically, this example demonstrates how a measure of the decay rate of an ion sample can be determined based on the extrapolated resolution of the ion sample, where the decay rate of the detection signal over time is dominated by collision effects, and the extrapolated resolution is the expected resolution of the detection signal.

[0093] Returning to the previously used general language, in embodiments of this disclosure, determining whether the resolution of the detection signal of the ion sample indicates that the decay rate of the detection signal of the ion sample over time is dominated by collision effects may include: determining whether the resolution of the detection signal is stable (e.g., constant, as in...) relative to the increasing number of sample ions in the sample ion cloud used to generate the detection signal of the ion sample. Figure 5 (In the stable platform region). Of course, as explained in detail in this article, SNR is only a measure that can be applied to its drawing resolution and can also be measured using ion count or signal strength. In the stable region, the gradient of resolution with respect to SNR can be below a threshold or approximately 0. This threshold can be set by the user or can be factory-set.

[0094] Determining whether the resolution of the detection signal of an ion sample indicates that the decay rate of the detection signal over time is dominated by collision effects can be achieved by determining whether the sample ion cloud used to generate the detection signal contains a sufficient number of sample ions to induce self-bundling. This can be determined by examining the mass spectrometry signal to identify signs of a sufficiently large number of ions in the ion pack, or by observing dephase cessation and exponential decay due to collision effects.

[0095] The extrapolated resolution of the ion sample can be determined by an extrapolation function that provides the expected resolution of the detection signal under conditions governed by collision effects. This can be referenced as follows. Figure 5 As described. For example, the extrapolation function can be determined based on multiple resolution measures and multiple signal strength measures, which are not obtained under conditions governed by collision effects. Therefore, the extrapolation function can be based on... Figure 1A , 1B The values ​​to the left of 3(III) and 5. Such values ​​can be used to infer the nature of the plateau on the right through appropriate analysis of the data. In some cases (and specifically when the data used for extrapolation does not cover the entire stable plateau), it is advantageous to base the extrapolation function on multiple resolution measures and multiple signal intensity measures of one or more calibrators. In this way, by taking into account the behavior of the calibrators, the behavior of sample ions at higher SNRs can be characterized more accurately.

[0096] The extrapolated resolution of the ion sample is determined by a fitting function of multiple resolution measures and multiple signal intensity measures, which provides the expected resolution of the detection signal under conditions dominated by collision effects. This can be described as per equation (II) or (III). Alternatively or additionally, an average resolution of multiple resolution measures and multiple signal intensity measures, preferably a rolling average or a weighted average, can be used, which provides the expected resolution of the detection signal under conditions dominated by collision effects. This can be described as per reference equation (I).

[0097] When the extrapolated resolution of an ion sample is determined based on a weighted average resolution of multiple resolution measures and multiple signal intensity measures, the multiple resolution measures may include one or more relatively high resolution measures and one or more relatively low resolution measures; and the one or more relatively high resolution measures are weighted to provide a greater contribution to the weighted average resolution compared to the one or more relatively low resolution measures. The multiple resolution measures can be corrected using: a fitting function of the multiple resolution measures and multiple signal intensity measures, which provides the expected resolution of the detection signal under collision-dominated conditions; and / or the average resolution of the multiple resolution measures and multiple signal intensity measures, preferably a rolling average or a weighted average, which provides the expected resolution of the detection signal under collision-dominated conditions. Therefore, the statistics of the analysis can be improved by ensuring that low-intensity peaks with high errors are not assigned high weights and do not significantly contribute to the error.

[0098] As previously described, the weighted average resolution can be based on the resolution of multiple isotopic variants of an ion sample and / or multiple resolution measures determined for a variety of different isotopic compositions. Analyzing multiple isotopes can provide a wide range of data points, which can reduce statistical errors. Isotopic analysis may be unavoidable, as isotopes will always be present in the sample unless they are intentionally separated to exclude isotopic variants. Since isotopic variants of a species tend to behave similarly and will elute from GC or LC approximately simultaneously, mass spectrometry analysis of samples eluted from GC or LC can capture data for multiple isotopic variants of any particular sample. Therefore, as previously described, it is preferable to determine multiple resolution measures for multiple retention times of elution spectra such as gas chromatography (GC) and / or liquid chromatography (LC).

[0099] Given the impact of ion counting on resolution, data from [source name] can be used. Figure 1A and 1BThe data is used to determine the confidence interval of CCS (or decay constant) measurements, and thus define the usability of CCS (or decay constant) values. For example, for relatively large error bands, such as >10-20%, CCS can only be used to distinguish between very different chemical classes (e.g., linear molecules against polyaromatic molecules, or lipids against peptides, etc.) or to analyze collision-induced unfolding of intact proteins or protein complexes. For low errors on the order of 1%, CCS can be used to reduce the search space within a single charge state of compounds in a single class, such as in lipidomics or bottom-up proteomics. Alternatively or additionally, CCS can be used as a quality control metric for labeling interfering peaks that may mask several peaks, as indicated by unexpected values ​​of CCS. For example, interfering peaks are shown in Figure 4 by Lyutvinskiy Y et al. (Adding colour to mass spectra: Charge Determination Analysis (CHARDA) assigns charge state to every ion peak. ChemRxiv. Cambridge: Cambridge Open Engage; 2021). Interference effects can be identified by irregularities in the CCS values ​​(and, for example, by variations in the CCS step size as the CCS is determined). Therefore, in a general sense, the methods described herein can further include using a measure of the decay rate of the ion sample to: classify the ion sample; and / or detect interfering species in the ion sample.

[0100] Figure 6 A third embodiment of this disclosure is shown, which is a preferred mass spectrometry system for implementing the methods described herein. The mass spectrometry system is an improved version of the Thermo Fisher Scientific Exploris system. TM The Thermo Fisher Scientific Exploris 480 mass spectrometer. The mass spectrometry system includes a high-capacity transfer tube 601, an electrically powered ion funnel 602, an EASY-IC internal calibration source 603, an advanced active beam guide (AABG) 604, a quadrupole mass filter 605, an independent charge detector 606, a C-trap 607, an ion routing multipole 608, and an ultra-high field Orbitrap mass analyzer 609, all of which are present in the existing Thermo Fisher Scientific Exploris 480 mass spectrometer. This embodiment of the mass spectrometry system includes pressure control within the Orbitrap compartment.

[0101] The mass spectrometry system further includes a pressure regulation assembly for mixing the quadrupole / orbital trap instrument. The mass spectrometry system includes a first vacuum region 621, in which the orbital trap mass analyzer 609 is located. The first vacuum region 621 is at a first vacuum level, typically ultra-high vacuum. The mass spectrometry system includes a second vacuum region 622 at a second vacuum level, which is a lower vacuum level than the first vacuum level (i.e., higher pressure). A quadrupole mass filter 605, an independent charge detector 606, a C-trap 607, and an ion routing multipole are located in the second vacuum region 622.

[0102] The mass spectrometry system includes a bellows 610 connected to a second vacuum region 622 near an ion routing multipole 608. The bellows 610 is connected to a valve 611, which is connected to a ConFlat (CF) T-joint 612. The T-joint 612 is connected to a first vacuum region 621. An ion meter with a heater gasket 613 is connected to a tube 614 terminating within the first vacuum region 621, allowing the ion meter 613 to measure the pressure within the first vacuum region. The bellows 610, valve 611, and T-joint 612 can constitute a first fluid connection between the first and second vacuum regions. This fluid connection can, of course, be any device that allows gas to be transferred from one vacuum region to another. Various combinations of tubes, pipes, and / or conduits can be employed.

[0103] Gas is introduced from the quadrupole compartment of the hybrid quadrupole / orbit trap into the mass analyzer 609 via C-trap 607, where a 3-5 x 10⁻⁵ m³ / h mass is formed by nitrogen (approximately 20%) from the ion source and nitrogen leaking from the multipole 610 of the ion route. -5 The pressure is mbar. Even if this pressure catastrophically surges into the UHV region of the quality analyzer 609, it will not cause high-pressure breakdown.

[0104] Unlike conventional leak lines from atmospheric pressure or even higher, this gas leak arrangement allows for the use of relatively simple valves 611 with larger cross-sections without the need for long, narrow capillaries to protect the system from accidental emissions. For example, a Parker 9 Series Miniature HV-compatible calibrator valve can be used under pulse width modulation (PWM) control. This results in greater tolerance to dust and errors. Preferably, the PWM operates based on the resulting UHV under feedback loop correction. For example, the reading of ion meter 613 can be used to control the amount of gas leaking through valve 611, and thus the pressure within mass analyzer 609. By controlling the pressure at which ions are analyzed in mass analyzer 609, the attenuation constant of the ions can be controlled to obtain accurate measurements of the attenuation constant and collision cross section. The mass spectrometry system can continuously monitor the pressure within the mass analyzer, and this feedback loop can be used to maintain a substantially constant pressure. However, using the techniques disclosed herein, if the pressure does deviate from the selected constant value, corrections can be incorporated into the calculation of the CCS and / or attenuation constant to account for pressure drift.

[0105] Therefore, returning to the previously used general terminology, a mass spectrometry system may include a controller configured to control the pressure within a first vacuum region based on the following: the pressure within the first vacuum region (e.g., to ensure the pressure within the first vacuum region is suitable for analysis); and / or a measure of the decay rate of the detection signal of the ion sample over time (e.g., to ensure the use of an appropriate transient detection time). The mass spectrometry system may further include a pressure sensor (e.g., an ion meter 613, but other types of pressure sensors, such as a Bayard-Alpert gauge), configured to measure the pressure within the first vacuum region and provide the measured pressure to the controller. The pressure in the trap may also be estimated based on the transient decay rate as described in US-9,460,905-B2, which is incorporated herein by reference in its entirety. The methods described herein may include controlling the pressure within a mass analyzer, and the mass spectrometry system may be configured to control the pressure within the mass analyzer to control: the decay rate of the detection signal of the ion sample over time; and / or the decay rate of the detection signal of the ion sample over time. The first vacuum region can be less than 3 x 10 -8 mbar(3x10) -6 Pa) and / or the second vacuum region is 1 x 10 -5 mbar(1x 10 -3 Pa) to 5 x 10 -5 mbar(5x 10 -3For the orbitrap region of a mass spectrometry system, the vacuum should be sufficiently good for long transients; therefore, the vacuum level can be set to provide a long mean free path, such as exceeding, for example, 1000 meters or even longer. Other pressures can be used. For example, in some cases, the initial vacuum region can be less than 5 x 10⁻⁶ Pa. -9 mbar and / or a second vacuum zone can be 2 x 10 -5 mbar, 3 x 10 -5 mbar or 4x 10 -5 mbar.

[0106] Preferably, gas is introduced through the same port used for UHV pressure measurement. However, precautions can be taken to ensure proper operation of the UHV meter. Figure 6 In this embodiment, this is achieved by connecting the ion meter 613 to the UHV compartment via a long tube 614, which is not directly connected to a gas leak because it can receive gas molecules at least after one or more reflections from the chamber wall. Therefore, in a general sense, the pressure sensor can be connected to the first vacuum region via a second fluid connection, which is not directly connected to the second vacuum region.

[0107] Although Figure 6 A specific advantage of this system is that it can use relatively inexpensive and simple valves 611 for specific gas leaks, but a variety of valves can be used. For example, high-quality valves (such as sapphire valves) can be used. In this case, it can accommodate gas leaks from atmospheric pressure or even higher pressures.

[0108] In the previously used general terminology, the mass analyzer of this disclosure is preferably a Fourier transform mass analyzer and more preferably an orbital trap mass analyzer or a Fourier transform ion cyclotron resonance mass analyzer. Various other multi-reflection electrostatic traps may also be used, such as any one or more of the following: Cassini trap, linear electrostatic trap, ConeTrap, etc. The second vacuum region (e.g., a vacuum region for gas leakage) may include any one or more (and optionally all) of the following: a quadrupole; a charge detector; an ion trap, such as a C trap; and / or an ion routing multipole. The mass spectrometry system may further include an ion routing multipole and / or a C trap, wherein fluid connections allow gas to be introduced from the second vacuum region into the first vacuum region via the ion routing multipole and / or the C trap.

[0109] The gas introduced from the second vacuum region into the first vacuum region can leak from the quadrupole of the mass spectrometry system.

[0110] In the methods and mass spectrometry systems described herein, it may be preferable to ensure that the pressure within the mass analyzer is the same for the analysis of the sample as it is for the analysis of the calibrator. However, the adjustment functions and scaling factors described herein can account for the effects of pressure. When the pressure remains constant, it is generally not necessary to correct the measured values ​​to account for pressure variations. However, pressure may vary randomly (e.g., due to temperature variations), so in some cases, it may be preferable to periodically inject the calibrator (e.g., Calmix, which contains approximately 10 species) to ensure reliable operation. Regardless of the calibrator used, it may have isotopes, and therefore calibration can also be performed using isotopic variant peaks. Different isotopes have different intensities and therefore will have different decay rates. Therefore, if three isotopes are present, analysis of the isotopes will result in extracted values ​​at three different points on the curves in Figures 1a, 1A, and 1B.

[0111] Preferably, the pressure is set to achieve the desired signal decay for a given analyte group (e.g., multiple charged peptides) over a given transient length. For example, the signal decay (i.e., the ratio of final intensity to initial intensity) of +2, +3, and +4 trypsin peptides is preferably 2-4 times at an MS1 ​​resolution setting of 60 K (corresponding to a 128 ms transient for a high-field Orbitrap analyzer). This corresponds to a certain decay of the calibrator ion as determined by previous experiments (e.g., 1.5 times over the same transient due to its lower m / z and +1 charge). Therefore, the pressure will be increased (e.g., by modulation, such as PWM control of valve 611) until the desired decay of the calibrator is achieved, and then the pressure is kept substantially constant for all experiments. During the duration of the experiment, it may be preferable to measure the calibrator occasionally (e.g., at the start of each LC / MS run) and adjust the m / z and CCS of the analyte according to any drift experienced.

[0112] right Figure 6 Many modifications to the arrangement will be apparent. For example, the vacuum region can be subjected to various pressures and can accommodate a wide variety of different components. Similarly, while Thermo Fisher Scientific's Exploris... TM A 480 mass spectrometer can be used, but other Fourier transform mass spectrometry systems can also be used. For example, a Q Exactive mass spectrometer can be used similarly. TM A hybrid quadrupole-Orbitrap mass spectrometer system. Various types of fluid connections can be provided to allow gas to leak from one vacuum region to another, and this disclosure is not limited to... Figure 6 Specific examples of bellows and valves are shown in the figure.

[0113] Figure 7Different species from the calibration mixture (195 m / z, 262 m / z, 524 m / z, and 1421 m / z) are shown at different pressure settings (4 x 10). -9 mbar, 1x 10 -9 mbar and 4x 10 -10 Transient signals (arbitrary units, au) at mbar. This type of data can be obtained from... Figure 6 The mass spectrometry system uses information about Figure 6 The pressure control described is provided. Figure 7 The decay of ion signals at different m / z values ​​of the calibration mixture over a transient duration of 512 ms is shown. It can be seen that the +2 charge state of the same peptide exhibits accelerated decay compared to the +1 charge state of the MRFA peptide.

[0114] Figure 7 The study showed accelerated decay of higher charge states for the same compound, which was attributed to higher center-of-mass collision energies. This trend was particularly evident in larger-scale studies of trypsin peptides from HeLa digests, as shown below.

[0115] The faster signal attenuation leads to a certain reduction in resolution after the Fourier transform, and therefore can be directly extracted from the RAW file saved by the mass spectrometer data acquisition system.

[0116] Figure 8 The figure illustrates the resolution of recordings of trypsin peptides of different masses in different charge states under elevated pressure versus standard low pressure operating conditions. Specifically, Figure 8 These are different levels of increased pressure (4 x 10). -9 "High UHV" in mbar refers to the standard low-pressure operating conditions (4) -10 A comparison of the resolution of records for different charge states at "low UHV" (mbar). If the resolution is not reduced, all points will be located diagonally (which would indicate that the low-pressure resolution and high-pressure resolution are the same). However, Figure 8 The dataset actually shows data points falling on the lower line parallel to the diagonal, indicating that, on average, the resolution under high pressure is lower than that under low pressure.

[0117] Since resolution is m / z related, it covers the full range of peptide masses measured, from 40,000 to 100,000. For lower recorded resolutions, the relative resolution decreases more significantly, which corresponds simply to the fact that higher mass for each given charge state leads to faster decay.

[0118] Figure 9 An overview of this dependence is provided by comparing the relative decrease in resolution for each charge state. The decrease in resolution is shown relative to the case without added gas. Figure 9 It shows the effects of different pressures Figure 8 The data is a summary (uncorrected for quality dependencies). Despite Figure 9 It does not contain quality-dependent features, but it has shown diagnostic values ​​for such measurements.

[0119] In the embodiments described herein, the detection signal of the ion sample can be obtained for the separated ion sample or in the form of a partial or full-range MS scan. An advantage of this disclosure is that intensity-dependent (e.g., SNR-dependent) corrections allow for the determination of the attenuation constant and CCS entirely online. While a wide mass range (e.g., hundreds of mass units) tends to produce lower intensities and thus exhibit less self-bundling, such values ​​may still require correction (e.g., due to space charge effects). When peaks are separated, there are more ions of a given species, resulting in more self-bundling (and higher resolution), and therefore potentially requiring less correction. In any case, the methods of this disclosure are fully compatible with both separation-quality analysis and full MS scanning.

[0120] It should be understood that embodiments of this disclosure can be implemented using a variety of different information processing systems. Specifically, while the figures and their descriptions provide exemplary computing systems and methods, these are presented merely for the purpose of providing useful reference in discussing various aspects of this disclosure. Embodiments can be performed on any suitable data processing apparatus, such as a personal computer, laptop computer, personal digital assistant, server computer, etc. Of course, for illustrative purposes, the descriptions of systems and methods have been simplified, and they are merely one of many different types of systems and methods that can be used. It should be understood that the boundaries between logical blocks are merely illustrative, and alternative embodiments may combine logical blocks or elements, or alternative functional decompositions may be applied to various logical blocks or elements.

[0121] It should be understood that the aforementioned functionality can be implemented as hardware and / or software as one or more corresponding modules. For example, the aforementioned functionality can be implemented as one or more software components executed by the system's processor. Alternatively, the aforementioned functionality can be implemented as hardware on one or more field-programmable gate arrays (FPGAs) and / or one or more application-specific integrated circuits (ASICs) and / or one or more digital signal processors (DSPs) and / or other hardware arrangements. The method steps included herein or implemented in the flowcharts described above can each be implemented with their corresponding modules. Furthermore, multiple method steps included herein or implemented in the flowcharts described above can be implemented together by a single module. Such modules and hardware can be integrated into a mass spectrometry system.

[0122] It should be understood that whenever the embodiments of this disclosure are implemented by a computer program, the storage medium and transmission medium carrying the computer program form aspects of this disclosure. The computer program may have one or more program instructions or program code that, when executed by a computer, perform the embodiments of this disclosure. As used herein, the term "program" can be a sequence of instructions designed to execute on a computer system and may include subroutines, functions, programs, modules, target methods, target implementations, executable applications, applets, server applets, source code, object code, shared libraries, dynamic link libraries, and / or other sequences of instructions designed to execute on a computer system. The storage medium may be a disk (such as a hard disk drive or floppy disk), an optical disk (such as a CD-ROM, DVD-ROM, or Blu-ray disc), or a memory (such as ROM, RAM, EEPROM, EPROM, flash memory, or portable / removable memory devices), etc. The transmission medium may be a communication signal, data broadcast, a communication link between two or more computers, etc.

[0123] This disclosure specifically relates to methods and apparatus for performing Fourier transform mass spectrometry (FTMS). In this disclosure, FTMS refers to mass spectrometry in which ions undergo periodic motion, which generates an image current, the frequency of which depends on the m / z of the ions. Mass spectra can be obtained by Fourier transforming the image current signal or by the Fourier transform, which is commonly referred to as transient. However, alternatively, other mathematical transforms or deconvolution methods can be used on the Fourier transform to obtain mass spectra from the image current signal, as known in the art. Examples of FTMS include Fourier transform ion cyclotron resonance and orbital trap mass spectrometry, the latter of which can be performed using an Orbitrap instrument. FTMS can also typically be performed using an electrostatic Kington ion trap.

[0124] Unless otherwise stated, each feature disclosed in this specification may be replaced by an alternative feature for the same, equivalent, or similar purpose. Therefore, unless otherwise stated, each disclosed feature is merely one instance of a series of equivalent or similar attribute features.

[0125] Furthermore, many variations can be made to the described embodiments, and these variations will be apparent to a skilled reader upon reading this specification. For example, while orbital traps are primarily described, the mass analyzer described herein can be any one or more of the following: an orbital trap mass analyzer; or a Fourier transform ion cyclotron resonance mass analyzer; and / or an electrostatic trap having an open configuration (e.g., utilizing only one or more reflections of the ion along one of the spatial dimensions) or a closed configuration (e.g., the ion changes direction multiple times along all dimensions during m / z separation).

[0126] As used herein (included in the claims), unless the context otherwise indicates, the singular form of a term herein should be understood to include the plural form, and vice versa, where the context permits. For example, unless the context otherwise indicates, singular references herein included in the claims, such as “a or an” (e.g., an ion or a detection signal), mean “one or more” (e.g., one or more ions or one or more detection signals). In the description and claims of this disclosure, the words “comprising,” “including,” “having,” and “containing,” as well as variations of the words such as “comprising” and “comprises” or similar, indicate that the described feature includes the following additional feature and is not intended to exclude the presence of other components. Furthermore, when a first feature is described as being “based on” a second feature, this means that the first feature is entirely based on the second feature, or at least partially based on the second feature.

[0127] The use of any and all instances or exemplary language (“for instance”, “such as”, “for example”, and similar language) provided herein is intended only to better illustrate this disclosure and, unless otherwise required, does not indicate any limitation on the scope of this disclosure. No language in this specification should be construed as indicating any unrequired element necessary for the practice of this disclosure.

[0128] Unless otherwise stated or required by the context, any steps described in this specification may be performed in any order or simultaneously. Furthermore, the fact that a step is described as being performed after another step does not preclude intermediate steps being performed.

[0129] All aspects and / or features disclosed in this specification can be combined in any combination, except for at least some mutually exclusive combinations of such features and / or steps. Specifically, preferred features of this disclosure apply to all aspects and embodiments of this disclosure and can be used in any combination. Similarly, features described in non-essential combinations can be used alone (not in combination).

Claims

1. A method for determining a measure of the decay rate of an ion sample being mass-analyzed in a mass analyzer using image current detection, the method comprising: The detection signal of the ion sample is received from the transient detection obtained using the mass analyzer, and the detection signal of the ion sample has a decay rate over time. as well as The measure of the decay rate of the ion sample is determined based on the extrapolated resolution of the ion sample. Under the condition that the decay rate of the detection signal of the ion sample over time is dominated by collision effects, the extrapolated resolution is the expected resolution of the detection signal. The extrapolation resolution of the ion sample is determined based on an extrapolation function that provides the expected resolution of the detection signal under collision-dominated conditions. The extrapolation function is determined based on multiple resolution measures and multiple signal intensity measures that are not obtained under collision-dominated conditions.

2. The method of claim 1, further comprising determining the measure of the decay rate of the ion sample only when one or more conditions are met, the one or more conditions including any one or more of the following: whether the peak of the detection signal is baseline resolved; whether the signal-to-noise ratio of the detection signal meets a threshold condition; and whether the peak of the detection signal belongs to an isotope cluster.

3. The method according to claim 1 or claim 2, wherein the extrapolated resolution of the ion sample is the resolution of the detection signal, provided that the expected resolution of the detection signal is stable relative to the increase in the number of sample ions in the sample ion cloud used to generate the detection signal of the ion sample.

4. The method of claim 1, wherein the extrapolation function is based on multiple resolution measures and multiple signal strength measures of one or more calibrators.

5. The method according to claim 1 or claim 2, wherein the extrapolated resolution of the ion sample is determined based on: a fitting function of a plurality of resolution measures and a plurality of signal intensity measures, the fitting function providing the expected resolution of the detection signal under conditions dominated by collision effects; and / or the average resolution of a plurality of resolution measures and a plurality of signal intensity measures, the average resolution providing the expected resolution of the detection signal under conditions dominated by collision effects.

6. The method of claim 5, wherein the average resolution is a rolling average or a weighted average.

7. The method of claim 5, wherein the extrapolated resolution of the ion sample is determined based on a weighted resolution of a plurality of resolution measures and a plurality of signal intensity measures, wherein: The plurality of resolution measures include one or more relatively high resolution measures and one or more relatively low resolution measures; and The one or more relatively high resolution metrics are weighted to provide a greater contribution to the weighted resolution compared to the one or more relatively low resolution metrics.

8. The method of claim 7, wherein the weighted resolution is based on the resolution of a plurality of isotopic variants of the ion sample.

9. The method of claim 4, wherein the plurality of resolution measures are determined for a plurality of different isotopic compositions and charge compositions.

10. The method of claim 4, wherein the plurality of resolution measures are determined for a plurality of retention times of the elution spectrum.

11. The method of claim 10, wherein the elution profile is a gas chromatography (GC) and / or liquid chromatography (LC) elution profile.

12. The method according to claim 1 or claim 2, wherein the measure of the decay rate of the ion sample is a decay constant or a collision cross section.

13. The method of claim 1 or claim 2, wherein the step of determining the measure of the decay rate of the detection signal of the ion sample over time is based on the peak width of the detection signal of the ion sample.

14. The method of claim 13, wherein the step of determining the measure of the decay rate of the detection signal of the ion sample over time takes into account the duration of the transient detection of the ion sample.

15. The method of claim 1 or claim 2, further comprising determining a plurality of measures of the decay rate of the ion sample.

16. The method of claim 15, further comprising determining a weighted measure of the decay rate of the ion sample by taking a weighted average of the plurality of measures of the decay rate of the ion sample.

17. The method of claim 16, wherein: The plurality of measures of the decay rate of the ion sample include one or more relatively high intensity measures of the detection signal of the ion sample and one or more relatively low intensity measures of the detection signal of the ion sample; and The one or more relatively high intensity measures of the detection signal of the ion sample are weighted to provide a greater contribution to the weighted average compared to the one or more relatively low intensity measures of the detection signal of the ion sample.

18. The method of claim 17, wherein the weighted average does not include one or more measures of the attenuation rate of the ion sample to which the intensity measure of the detection signal of the ion sample is below a threshold.

19. The method of claim 16, wherein the plurality of measures of the decay rate of the ion sample are determined for a plurality of different isotopic compositions.

20. The method of claim 19, wherein the weighted average is based on a measure of the decay rate of a plurality of isotopic variants of the ion sample.

21. The method of claim 15, wherein the plurality of measures of the decay rate of the ion sample are determined with respect to a plurality of retention times in the elution spectrum.

22. The method of claim 21, wherein the elution profile is a gas chromatography (GC) and / or liquid chromatography (LC) elution profile.

23. The method according to claim 1 or claim 2, wherein: The detection signal of the ion sample is obtained for the separated ion sample; or The detection signal of the ion sample was obtained in the form of a full MS scan.

24. The method according to claim 1 or claim 2, wherein the mass analyzer is any one or more of the following: an orbital trap mass analyzer; a Fourier transform ion cyclotron resonance mass analyzer; an electrostatic trap.

25. The method of claim 24, wherein the quality analyzer is an electrostatic trap having an open or closed configuration.

26. The method of claim 1 or claim 2, further comprising using the measure of the decay rate of the ion sample to: classify the ion sample; and / or detect interfering species in the ion sample.

27. The method of claim 1 or claim 2, further comprising controlling the pressure within the mass analyzer to control: the decay rate of the detection signal of the ion sample over time; and / or the decay rate of the detection signal of the ion sample over time.

28. The method of claim 1 or claim 2, wherein the mass analyzer is located in a first vacuum region at a first vacuum level, the method further comprising selectively introducing gas from a second vacuum region at a second vacuum level into the first vacuum region, thereby controlling the pressure within the first vacuum region, the second vacuum level being a vacuum level lower than the first vacuum level.

29. A computer program comprising instructions that, when executed by a processor, cause the processor to perform the method according to any one of claims 1-28.

30. A computer-readable medium having a computer program stored thereon according to claim 29.

31. A mass spectrometry system comprising a mass analyzer and a processor, the processor being configured to perform the method according to any one of claims 1 to 28.

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