DEVICE FOR MASS SPECTRAL DATA ANALYSIS

Abstract

Device for analyzing peak data generated from mass signals recorded by a mass spectrometric system (100, 100'), comprising: a streaming device (200) which includes a first network interface (210) and is configured to (a) generate peak data from the recorded mass signals or to receive peak data generated externally from the recorded mass signals, (b) group the peak data into independently processable data packets relating to different processing tasks, and (c) distribute the data packets in different task-specific streams over the first network interface (210) to a network (400); and at least one analysis device (300) which includes a second network interface (310) and is configured to (a) retrieve the data packets of the various task-specific streams from the network (400) via the second network interface (310), (b) perform the processing tasks on the retrieved data packets to generate result data, (c) package the result data into result data packets, and (d) distribute the result data packets to the network (400) via the second network interface (310).

Description

Field of invention

[0001] The invention relates to devices for analyzing mass spectral data acquired by a mass spectrometric system, in particular a mass spectrometric system comprising a mobility separator and a mass analyzer, and methods for analyzing mass spectral data using the device. Background of the invention

[0002] Proteomics is currently a key technology in the life sciences and an approach to understanding the molecular mechanisms underlying normal and disease phenotypes and identifying critical diagnostic and prognostic biomarkers. Proteomics seeks to identify proteins potentially present in samples and to assess protein abundance, localization, post-translational modifications, isoforms, and molecular interactions. As a discipline, proteomics has grown at the intersection of instrumental technology, biochemistry, and bioinformatics, with an emphasis on high throughput and reduced user bias. Accordingly, the technologies used are diverse but almost always employ coupled techniques, such as liquid chromatography / mass spectrometry.

[0003] Furthermore, metabolomics has become an increasingly important research approach in the life sciences in recent years. The term "metabolomics" describes the analytical detection of low molecular weight metabolomic compounds in a biological system, for example, in a cell, tissue, or body fluids such as urine or blood plasma. The entirety of these compounds, the metabolomes, consists of primary and secondary metabolites of endogenous metabolism, such as amino acids, sugars, lipids, nucleosides, steroids, alcohols, etc., as well as exogenous substances such as drugs. Metabolomics, like proteomics, focuses on complex analyte mixtures with highly dynamic abundance ranges.

[0004] Mass spectrometric systems have been developed that couple a liquid chromatography (LC) apparatus, an ion mobility separator, and a time-of-flight mass analyzer. Systems that couple different separation devices are often called hybrid systems. Fig. Figure 1 shows a scheme of an exemplary mass spectrometric system 100 and a device 10 for recording and analyzing mass spectral data according to the previous state of the art.

[0005] The mass spectrometric system 100 includes a liquid chromatography apparatus 130, an ion source 121, an ion mobility separator 144, a quadrupole mass filter 150, a fragmentation cell 160 and a time-of-flight (TOF) mass analyzer 170.

[0006] The ion mobility separator 144, for example, can be a time-of-flight (TIMS) storage ion mobility separator that can be operated in a parallel collection mode. In this mode, ions are collected in an upstream part of the ion mobility separator or an upstream ion trap (not shown), while previously collected ions are analyzed in a downstream part of the ion mobility separator in parallel time. The time-of-flight (TOF) mass analyzer 170 is typically a time-of-flight analyzer with orthogonal ion injection (OTOF).

[0007] The liquid chromatography apparatus 130 is coupled to the ion source 121, which is typically an electrospray ion source operating at atmospheric pressure. Other types of ion sources are possible. Ions generated in chamber 120 are introduced via a transfer capillary 141 into a first vacuum chamber 140 and deflected into a high-frequency funnel 143 by means of a repulsive DC electrical potential applied to a deflecting electrode 142. The high-frequency funnel 143 collects the ions conveyed through the transfer capillary 141 and / or the ions generated by an additional MALDI source in the chamber 140 (not shown) and directs them to the ion mobility separator 144. Ions released by the ion mobility separator 144 according to their mobility are directed to the quadrupole mass filter 150, which either conveys ions onward or selects ions according to their mass.The ions passing through the quadrupole mass filter 150 are directed to a fragmentation cell 160 to generate fragment ions. Fragmentation can be induced by collision-induced dissociation (CID) or by any other known method. Fragmentation can be switched on or off via instrumental parameters. Precursor ions can be stored in the fragmentation cell 160 without being fragmented, as can fragment ions when fragmentation is activated.

[0008] The mass spectrometric system is controlled by the device 10 via the control line 12. The device 10 contains a central processing unit (CPU), a recording unit 13, a memory 14, and a graphics processing unit (GPU) 15. The components of the device 10 are connected via a local interface 16, for example, a PCI Express interface bus. The recording unit 13 is connected to an ion detector 171, which is located at the end of the flight path and is configured to generate a pulsed electron stream for ions striking the ion detector 171. Typically, the ion detector includes a secondary electron multiplier, such as a microchannel plate detector.The recording unit contains an analog-to-digital converter for digitizing the pulsed electron stream and a processing unit to generate peak data from the digitized stream, for example by using a real-time peak search algorithm applied to the digitized stream.

[0009] The TOF mass analyzer 170 has such a high acquisition rate for mass spectra that many mass spectra are acquired during a single mobility separation. The peak data is a list of ordered pairs, where each pair represents a mass signal from an acquired mass spectrum and includes a mass-related value (e.g., time of flight) and an intensity-related value. The peak data acquired for all mass spectra during a single mobility separation are stored in a file-based representation in memory 14, and the data structure is determined by the temporal sequence of data acquisition. US Application No. 16 / 367,296 (published as US 2020 / 0303034 A1) discloses that the cores of a GPU can be used to process the peak data in parallel.

[0010] Mass spectrometric systems with a mobility separator enable the acquisition of fragment mass spectra in a data-dependent mode at the highest rates, as shown in the publication by Meier et al. (Mol Cell Proteomics; 2018 Dec; 17(12):2534-2254: “Online Parallel Accumulation-Serial Fragmentation (PASEF) with a Novel Trapped Ion Mobility Mass Spectrometer”). Furthermore, they are very well suited for acquiring mixed fragment mass spectra in a data-independent mode, which can be processed (deployed) based on the mobility information, as shown in the publication by Meier et al. (Nat Methods; 2020 Dec; 17(12): 1229-1236: “diaPASEF: parallel accumulation-serial fragmentation combined with data-independent acquisition”).

[0011] All mass spectrometric systems with high spectral acquisition rates are suitable for detailed analysis of complex samples in proteomics and metabolomics. Increased acquisition rates of mass spectra (MS or MS1) and fragment mass spectra (MS2) have made it possible to identify and quantify more compounds during a single analysis, but have also significantly increased the amount of mass spectral data to be analyzed. The amount of mass spectrometric data is similarly increased by mass spectrometric imaging, where an ion source is configured to generate ions from many positions on a two-dimensional sample, such as a tissue section, so that the number of samples, and thus the number of acquired mass spectra and fragment mass spectra, is at least equal to the number of grid points in the mass spectrometric image.

[0012] Advances in the instrumental side of mass spectrometry systems necessitate sophisticated devices for analyzing mass spectral data that can keep pace with the high acquisition rates of these instruments. These devices could represent a significant step toward the use of mass spectrometry systems not only in research but also in routine clinical applications.

[0013] Further devices for analyzing peak data generated from mass signals acquired by a mass spectrometric system are disclosed, for example, in patent applications WO 2019 / 028 004 A1 and WO 2019 / 243 836 A1. In this context, WO 2019 / 028 004 A1 describes a device for detecting the presence of a substance of interest in a sample, and WO 2019 / 243 836 A1 describes a method for identifying possible fragmentation pathways of a molecule based on mass spectrometry data of the molecule. Summary of the invention

[0014] The invention provides a device for analyzing peak data generated from mass signals acquired by a mass spectrometric system. The device comprises a streaming device and at least one analysis device. The streaming device includes a first network interface and is configured to (a) generate peak data from the acquired mass signals or to receive externally generated peak data from the acquired mass signals, (b) group the peak data into independently processable data packets relating to different processing tasks, and (c) distribute the data packets in different task-specific streams over a network via the first network interface.The at least one analysis device includes a second network interface and is configured to (a) retrieve the data packets of the various task-specific streams from the network via the second network interface, (b) for at least one of the various task-specific streams, perform the processing task on the data packet retrieved from that task-specific stream in order to generate result data, (c) package the result data into a result data packet, and (d) distribute the result data packet to the network via the second network interface.

[0015] The peak data is a series of tuples, where each tuple represents a single mass signal from a recorded mass spectrum, with a tuple defined as a finite, ordered list of values. Each data packet is a subset of the peak data, and "independently processable" means that the analysis device can perform the processing task on a single data packet without additional peak data. The network is not a local computer bus implemented in the streaming device. The intersection set between a first data packet and a second data packet of a task-specific stream must not be empty; that is, a single tuple of the peak data can exist in different task-specific streams.

[0016] The at least one analysis device can contain a plurality of processing units, each configured to perform the processing task simultaneously on different data packets. The at least one analysis device preferably contains more than 10, 100, 500, or 1000 processing units. Preferably, the at least one analysis device includes a main processor (CPU), global memory, and a graphics processing unit (GPU). The CPU is configured to store retrieved data packets of the task-specific stream in the global memory, convert the data packets into a GPU-compatible format, and forward the converted data packets to the GPU cores, which perform the processing task on the converted data packets simultaneously. The CPU, GPU, and global memory are connected via a local computer bus, for example, a PCI Express bus.

[0017] The device can contain a multitude of analyzers configured to perform the processing task simultaneously on different data packets. Preferably, the device contains more than 2, 5, 10, or 20 analyzers. Each data packet is preferably distributed with a header containing an identification key and / or information regarding the analyzer that is to retrieve and process the data packet. The analyzers can further be configured to retrieve result data packets from other analyzers, with the result data of an analyzer containing information that a particular data packet is being processed by that analyzer. Such a feedback stream can help organize the distribution of the data packets across multiple analyzers.

[0018] The streaming device is configured to group the peak data into independently processable data packets related to different processing tasks and to distribute the data packets across the network in various task-specific streams. Each data packet can be distributed with a header containing information about the processing task that the data packet is scheduled to perform. The intersection set between a first data packet of a task-specific stream and a second data packet of a different task-specific stream must not be empty; that is, a single tuple of the peak data can exist in different task-specific streams.

[0019] Each data packet can be distributed with a header containing operating parameters of the mass spectrometric system and / or acquisition times of the mass signals represented in the data packet, relating to retention times of the corresponding analytes eluted by a separation device coupled to the mass spectrometric system.

[0020] The streaming device can be configured to generate each data packet of a task-specific stream immediately after the peak data required for the data packet is available, so that the data packets of the task-specific stream are distributed to the network in real time.

[0021] In one embodiment, the streaming device includes a recording unit that is connected to and configured with a local computer bus of the streaming device and an ion detector of the mass spectrometric system to generate peak data from the mass signals detected by the ion detector. Preferably, the ion detector generates a pulsed electron stream, and the recording unit includes an analog-to-digital converter for digitizing the pulsed electron stream and a processing unit for generating the peak data from the digitized signal, for example, by a real-time peak-search algorithm. The ion detector may include a secondary electron multiplier, for example, a microchannel plate.The recording unit can forward a single tuple or groups of tuples to a memory of the streaming device, where, for example, each group can contain the tuples of a single recorded mass spectrum or the tuples of a multitude of recorded mass spectra.

[0022] In another embodiment, the streaming device is connected to an acquisition unit of the mass spectrometric system via the network or an additional data connection. The acquisition unit is connected to an ion detector of the mass spectrometric system and configured to (a) generate peak data from the mass signals detected by the ion detector and (b) forward the peak data to the streaming device via the network interface or the additional data connection. The peak data are forwarded as packets, with each packet containing, for example, a single tuple, all tuples of a single acquired mass spectrum, or all tuples of a plurality of acquired mass spectra.

[0023] The streaming device can further be configured to retrieve the result data packet from the network and organize it according to a predetermined result data protocol. Preferably, the streaming device is connected to the mass spectrometric system and configured to modify its operation depending on the result data of the retrieved result data packets. The streaming device can also be configured to combine the peak data and the retrieved result data into independently processable data packets related to an additional processing task, and to distribute the data packets in an additional task-specific stream over the first network interface to a network.

[0024] The device may also include an auxiliary device configured to retrieve the result data packet from the network and organize it according to a predetermined result data protocol. This auxiliary device may be connected to the mass spectrometry system and configured to modify its operation based on the retrieved result data packets. The auxiliary device, or streaming device, may also serve as an output device for a user.

[0025] The network can be part of the device. Preferably, the network is a local area network (LAN) and / or preferably uses an Ethernet protocol. The network can also use an internet protocol (IP), with the first network interface preferably being assigned a fixed network IP address to enable a direct network connection. The analysis devices can further be configured to communicate with other sources (e.g., databases or cloud services) over the network to query additional non-peak data required to perform processing tasks.

[0026] The invention provides methods for peak data analysis using a device according to the invention and, in particular, methods for generating the task-specific streams.

[0027] The task-specific streams may, for example, relate to (a) precursor searches in mass spectra, (b) analyte identification, such as peptides, proteins, other biomolecules or metabolites from fragment mass spectra, (c) the assignment of fragment mass signals from mixed fragment mass spectra containing fragment mass signals from different precursor ion types to one of the precursor ion types, or (d) the detection of post-translationally modified peptides from fragment mass spectra.

[0028] The device according to the invention can analyze peak data generated from mass signals acquired by different types of mass spectrometric systems. These mass spectrometric systems include an ion source and a mass analyzer, for example, a time-of-flight mass analyzer, an electrostatic ion trap, an RF ion trap, or an ion cyclotron frequency ion trap. Preferably, the mass spectrometric system further includes an ion mobility separator (IMS) and a fragmentation cell, wherein the peak data are a series of ordered triples (3-tuples). Each ordered triple represents a single mass signal from an acquired mass spectrum and contains a mobility-related value (e.g., IMS scan time or spectrum number in the IMS scan or calibrated mobility), a mass-related value (e.g., time of flight or calibrated mass), and an intensity-related value (e.g., maximum value of the mass signal).The ion mobility separator is preferably arranged between the ion source and the fragmentation cell. Optionally, the preferred mass spectrometric system can include a mass filter, which is preferably arranged between the ion mobility separator and the fragmentation cell. The fragmentation cell is preferably arranged between the ion mobility separator and the mass analyzer, or between the mass filter and the mass analyzer. Furthermore, a separation device, such as a gas or liquid chromatography apparatus or an electrophoretic apparatus, can be part of or coupled to the mass spectrometric system.

[0029] The ion source generates ions, for example, using spray ionization (e.g., electrospray ionization (ESI) or thermal spray ionization), desorption ionization (e.g., matrix-assisted laser desorption (MALDI) or secondary ionization), chemical ionization (CI), photoionization (PI), electron impact ionization (EI), or gas discharge ionization. The ion mobility separator can be, for example, a drift-time IMS (DTIMS), a traveling-wave IMS (TWIMS), or a trapped IMS (TIMS). The ions can be, for example,In the fragmentation cell, fragmentation can occur through collision-induced dissociation (CID), surface-induced dissociation (SID), photodissociation (PD), electron capture dissociation (ECD), electron transfer dissociation (ETD), electron transfer collisional dissociation (ETcD), activated ion electron transfer dissociation (AI-ETD), or fragmentation through reactions with highly excited or radical neutral particles.

[0030] The ion source can be configured to generate ions from different locations within a two-dimensional sample, such as a tissue section. Therefore, the peak data can be a series of ordered quintuples (5-tuples), where each quintuple represents a single mass signal within a recorded mass spectrum and includes two coordinate values ​​of the ionization position on the sample, a mobility-related value, a mass-related value, and an intensity-related value. Without mobility separation, the peak data can be a series of ordered quadruples (4-tuples), where each quadruple represents a single mass signal within a recorded mass spectrum and includes two coordinate values ​​of the ionization position on the sample, a mass-related value, and an intensity-related value.

[0031] The device according to the present invention is preferably connected to a mass spectrometric system comprising an IMS separator, a mass filter, a fragmentation cell, and a time-of-flight (TOF) mass analyzer with orthogonal ion injection. The spectral acquisition rate of the TOF mass analyzer is high enough to acquire many mass spectra during a single IMS separation (cycle). The peak data form a mass-mobility map, with one axis displaying a mobility-related value and a perpendicular axis displaying the mass-related value. In an MS1 ​​cycle, the fragmentation of the ions separated in the IMS separator is deactivated. In an MS2 cycle, the fragmentation of the ions separated in the IMS separator is activated. During an MS2 cycle, the mass filter can be operated such that only ions within a mass window are passed from the ion mobility separator to the fragmentation cell.The mass window position can be changed incrementally (with or without overlap between successive mass windows) or continuously (with overlap between successive mass windows) during the MS2 cycle. The width of the mass window can be adjusted to allow a single ion species or a limited mass range of ion species to pass through.

[0032] A first task-specific stream relates to the identification of suitable precursor ion species in a mass mobility map of an MS 1 cycle. These identified precursor ion species can be used in a subsequent MS2 cycle for data-dependent analysis (DDA) or targeted analysis of predetermined ion species, for example in parallel reaction monitoring (PRM).

[0033] The data packets are generated from peak data of a mass-mobility map of the MS1 cycle. The mass-mobility map is divided into regions, each with a defined mobility and mass range. For DDA, the regions can cover the mass-mobility map where the presence of any ion species is expected. The different regions may or may not overlap along the mobility and / or mass direction. For targeted analysis, the regions cover the mass-mobility map only where the predetermined ion species can be present. Each data packet contains a subset of the peak data, with each subset containing ordered triples of the peak data whose mobility and mass values ​​fall within one of the regions.The streaming device generates the various data packets and transmits them to the analysis devices, which perform the processing task on the data packets and distributes the resulting data, containing the mobility and mass of the appropriate precursor ion species, across the network. The streaming device retrieves the resulting data packet from the network and, in a subsequent IMS separation, controls the mass filter to isolate and fragment the selected precursor ion species, or a subset thereof, within the mass filter. Typically, several MS2 cycles follow an MS1 ​​cycle to analyze all appropriate precursor ion species identified as a result of the first task stream.

[0034] A second task-specific stream relates to the identification of an ion species using the mass signals of fragment mass spectra acquired during the subsequent IMS separation(s) of the MS2 cycle(s) mentioned above.

[0035] As explained above, the streaming device can control the mass filter during an MS2 cycle so that individual precursor ion species are sequentially isolated and fragmented within the mass filter. This means that the mass window position of the mass filter is adjusted to accommodate different precursor ion species during an IMS separation. Typically, the mass filter is set to the mass of a single precursor ion species for a duration sufficient to acquire many fragment mass spectra for that precursor ion species. Each data packet contains the peak data from the many fragment mass spectra of a single isolated precursor ion species. If the same precursor ion species is isolated in two or more MS2 cycles, the corresponding data packet can contain the peak data from the many fragment mass spectra of that precursor ion species acquired in those two or more MS2 cycles.

[0036] Identification is performed by an analyzer and may involve comparing the measured fragment mass signals (corresponding to the triplet of the data packet) with reference fragment mass spectra or computer-generated fragment spectra of known substances. The reference fragment mass spectra and computer-generated fragment spectra are additional data required for identification and can be stored locally in the analyzers or retrieved from external sources via the network.

[0037] Preferably, the data packet is distributed with a header containing the mass position of the mass filter during the acquisition of the fragment mass spectra (i.e., the mass of the precursor ion). Each data packet contains a series of triples, where each triplet represents a fragment mass signal of the precursor ion species and includes a mobility-related value of the fragment mass signal, as well as a mass-related value and an intensity-related value. Since the mobility-related value of the fragments matches the mobility-related value of the corresponding precursor ion species, the analytical instrument that processes the data packet possesses information about the mass and mobility of the precursor ion species. This information about the mass and, optionally, the mobility of the precursor ion species can be used to reduce the search space for comparison during the identification process.For example, the data packets can be processed by a multitude of processing units of an analysis device, and each of these processing units can be assigned, for example, a limited search space with respect to the mass and, optionally, mobility of the precursor ion loci. Each of the processing units stores only the additional data for a limited subset of the precursor ions.

[0038] The data packets can be processed by a variety of analyzers, and each of these analyzers can be assigned, for example, to a limited search space with respect to the mass and, optionally, the mobility of the precursor ion species. The streaming device can forward the data packets to the analyzers according to the mass and mobility of the precursor ion species.

[0039] The result stream of identifications can be forwarded from the analyzers to the streaming device. For example, if a result from one of the data packets does not lead to a sufficient identification, the streaming device can redefine the associated precursor ion species with adjusted parameters (e.g., higher collision energy for CID) or collect fragment mass spectra of the precursor ion species in further MS2 cycles. In bottom-up proteomics, a precursor ion species refers to a digest peptide of a protein, and the stream-specific task can also include protein identification. For example, a result stream from the analyzers might contain computer-generated digest peptides of all identified proteins, with a single result data packet containing all computer-generated digest peptides of a single identified protein.The streaming device can use this result stream to update a list of precursor ion species for which fragment mass spectra are to be acquired, excluding the computer-generated digest peptides of identified proteins from the list, as they no longer need to be isolated and fragmented.

[0040] A third task-specific stream relates to the determination of the presence of a marker ion in fragment mass spectra.

[0041] The preferred mass spectrometric system comprises an IMS separator, a mass filter, a fragmentation cell, and a time-of-flight (TOF) mass analyzer with orthogonal ion injection. It can be operated in a mode where the mass filter is switched off or set to a wide mass window to allow many precursor ion species to pass through to the fragmentation cell. The acquired fragment mass spectra are mixed fragment mass spectra, meaning that fragment mass signals from different precursor ion species are represented in a single fragment mass spectrum.

[0042] The peak data of the mixed fragment mass spectrum acquired during an MS2 cycle form a mass-mobility map, for which one axis represents a mobility-related value and a perpendicular axis represents a mass-related value. A strip of the mass-mobility map, centered around a characteristic mass and extending along the mobility axis, is divided into regions. The regions covering the strip may or may not overlap. Each data packet contains a subset of the peak data, with each subset containing those ordered triples of peak data whose mobility-related and mass-related values ​​fall within one of the regions covering the mass-mobility map strip. The characteristic mass could, for example, be that of the immonium ion at m / z 216.This fragment ion is commonly used as a "reporter ion" or "trigger fragment" for the identification of tyrosine-phosphorylated peptides. The stream-specific task can therefore be used to determine whether a tyrosine-phosphorylated peptide is present during an MS2 cycle and where it is located along the mobility axis in the mass-mobility map. The resulting data from the task-specific stream can be combined with peak data from a previously acquired MS1 cycle to generate a combined stream for identifying the corresponding precursor ion species in the MS1 cycle peak data, or to control the mass window of the mass filter in one or more subsequent IMS separations to limit the number of potential candidates for the corresponding precursor ion species.

[0043] A fourth task-specific stream relates to the identification of an ion species using the mass signals of fragment mass spectra acquired during an MS2 cycle. Unlike the second task-specific stream, the fragment mass spectra are mixed fragment mass spectra, and the analysis is a so-called data-independent analysis (DIA). The mass filter is not adjusted to allow individual precursor ion species to pass through, but rather to allow many precursor ion species to pass through. The mass window typically has a width between 10 and 50 mass units or Daltons. The position of the mass filter's mass window is changed stepwise during an IMS separation.

[0044] A data packet contains the peak data of the mixed fragment mass spectra acquired during a single step of the mass filter. Identification is performed by an analyzer and may involve comparing the measured fragment mass signals (corresponding to the triplets in the data packet) with reference fragment mass spectra or computer-generated fragment spectra of known substances. The reference fragment mass spectra and the computer-generated fragment spectra are additional data required for identification and can be stored locally in the analyzers or requested from external sources via the network. The third and fourth task-specific streams can be generated and analyzed in parallel.

[0045] In a specific DIA of the mass spectrometric system, mass mobility images are acquired in multiple MS2 cycles, with the mass window position of the mass filter being changed during each MS2 cycle and also shifted between subsequent MS2 cycles. Preferably, the mass window position is changed continuously during a single MS2 cycle. The peak data of the mixed fragment mass spectra acquired during a single MS2 cycle span a mass mobility image. A fifth task-specific stream relates to the determination of the presence and / or intensity of a specific fragment ion species in the many mass mobility images, providing a pattern that can be used to associate the fragmention with a precursor ion species. The data packets of the fifth task-specific stream are generated from the peak data of the many mass mobility images.For this task-specific stream, the peak data are a series of ordered quadruples (4-tuples). Each ordered quadruple represents a single mass signal from a recorded mass spectrum and includes the MS2 cycle number, a mobility-related value, a mass-related value (e.g., flight time or calibrated mass), and an intensity-related value. Each of these mass-mobility maps is divided into regions, with the size and position of the regions being identical for all mass-mobility maps. Each region covers a limited mobility and mass range of the mass-mobility map. Different regions may or may not overlap. Each data packet contains all the peak data from the many mass-mobility maps whose mobility-related and mass-related values ​​fall within one of the regions.

[0046] As described in the embodiments above, the data packets of a task-specific stream can contain all peak data whose mobility-related and mass-related values ​​fall within a limited range of a single mass mobility map or many successive mass mobility maps. The mass mobility map(s) can be the map(s) acquired in an MS1 ​​or MS2 cycle or cycles. However, it is also possible for the data packets of a stream to contain all peak data whose mobility-related and mass-related values ​​fall within one of the two or more non-adjacent ranges of a single mass mobility map or many successive mass mobility maps.

[0047] A first advantage of the present invention is that the acquisition unit (which is part of the device or the mass spectrometric system) is decoupled from devices for analyzing the peak data generated from the acquired mass signals. The process of generating the peak data from the mass signals is therefore not limited by computer resources required for peak data analysis, in particular not by access to shared memory via a local computer bus used by both systems.

[0048] A second advantage of the present invention is that the processing and analysis of the peak data is not based on a file-based representation of the peak data; that is, the peak data is not stored in a structure determined by the chronological order of its acquisition, but rather in a task-based representation. The streaming device generates task-specific streams of data packets, each representing a reduced subset of the peak data to which specific analysis can be applied without additional peak data. The analysis devices do not need to extract peak data from the file-based representation; instead, they are supplied with meaningful digital data packets.

[0049] A third advantage of the present invention is that the device is horizontally scalable by adding further analysis devices, and that it can be further adapted to integrate other resources via the network, such as cloud services or internet services. Brief description of the drawings

[0050] For a better understanding of the invention, reference is made to the following illustrations. The elements in the illustrations are not necessarily shown to scale, but are primarily intended to illustrate the principles of the invention (mostly schematically). In the illustrations, corresponding elements in the different views are identified by the same reference numerals. Fig. Figure 1 shows a mass spectrometric system 100 and a device 10 for analyzing mass spectral data according to the current state of the art. Fig. Figure 1 shows a first embodiment of a device for peak data analysis according to the invention, which is coupled to a mass spectrometric system 100 and includes a streaming device 200, an analysis device 300 and a network 400, wherein the analysis device 300 includes a memory 304 for storing the data packets that are generated by the streaming device 200 and received by it via the network 400. Fig. Figure 1 shows a second embodiment of a device for peak data analysis according to the invention, which is coupled to a mass spectrometric system 100 and includes a streaming device 200, an analysis device 300 and a network 400, wherein the analysis device 300 includes a GPU 305 with many cores and local memory for storing data packets generated by the streaming device 200 and received by it via the network 400. Fig. Figure 1 shows a third embodiment of a device for peak data analysis according to the invention, which is coupled to a mass spectrometric system 100' and includes a streaming device 200, two analysis devices (300, 300') and a network 400. The acquisition unit 103 is integrated into the mass spectrometric system 100' and coupled to the streaming device 200 via a network 400. Detailed description

[0051] While the invention has been presented and explained with reference to a number of embodiments, those skilled in the field will recognize that various changes in form and detail can be made to it without deviating from the scope of the technical teaching defined in the attached claims.

[0052] Fig. Figure 1 shows a first embodiment of a device for peak data analysis according to the invention, which is coupled to a mass spectrometric system 100 and includes a streaming device 200, an analysis device 300, and a network 400. The mass spectrometric system 100 can, for example, be the one described in Figure 1. Fig. The reproduced IMS-q-OTOF system should be.

[0053] The streaming device includes a CPU 201, an acquisition device 203, and a memory 204, all interconnected via a local PCI Express bus 216. The streaming device 200 controls the mass spectrometry system 100 via a control line 202. The acquisition unit 203 is connected to an ion detector 171, which provides a pulsed analog current for ions arriving at the ion detector 171. The acquisition unit 203 includes an analog-to-digital converter for digitizing the pulsed electron current and a processing unit for generating peak data from the digitized current. The peak data consists of a list of ordered triples, where each ordered triplet represents a single mass signal from an acquired mass spectrum and includes a mobility-related value (e.g., IMS scan time or spectrum number in the IMS scan or calibrated mobility), a mass-related value (e.g.,The data contains a flight time or calibrated mass) and an intensity-related value. The peak data for all (fragment) mass spectra acquired during a single mobility separation are stored in a file-based representation in memory 204. The streaming device processes the peak data and generates many data streams (S1, S2, ... Sn), each of which contains many data packets (S1-Pi; S2-Pj; ... Sn-Pk with i, j, k = 1 .... N). The data packets (S1-Pi; S2-Pj; ... Sn-Pk) are sent to network 400 via a network interface 210.

[0054] The analyzer 300 is a separate device and is not connected to the local PCI Express bus 216 of the streaming device 200. It contains a CPU 301, a memory 304, a GPU 305, and a local PCI Express bus 316 and is configured to receive the data packets (S1-Pi; S2-Pj; ... Sn-Pk) of the many streams (S1, S2, ... Sn) from the network 400 via a network interface 310. The received data packets are stored in different stream-specific partitions (304-1, 304-2, ... 304-n) of the memory 304. The CPU 301 transforms the data packets so that they can be assigned to and processed by the different cores of the GPU 305. The cores of the GPU 305 access the converted, stream-specific data packets (S1-Pi; S2-Pj; ... Sn-Pk) via the local PCI bus 316, which are stored in the partitions (304-1, 304-2, ... 304-n) of memory 304.The data packets are processed or analyzed in parallel by the cores in the GPU 305.

[0055] The analyzer 300 can communicate with additional sources (e.g., databases or cloud services, not shown) via the network 400 to retrieve additional data or services (e.g., prediction of impact cross-sections related to ion mobility via the Mason-Schamp equation) that are not peak data stored in the memory of the streaming device 200. For example, the same data packet can be assigned to different cores of the GPU 305, while these cores are supplied with different additional data from the sources for parallel analysis of the data packets, depending on the specific additional data. The analysis results from the processing units of the analyzer 300 can be sent via the network to one or more additional devices (not shown) used to organize the results for a user.

[0056] Fig. Figure 1 shows a second embodiment of a device for peak data analysis according to the invention, which is coupled to a mass spectrometric system 100 and includes a streaming device 200, an analysis device 300 and a network 400.

[0057] As in the first embodiment, the mass spectrometric system 100 can, for example, perform the following functions: Fig. The IMS-q-OTOF system is represented. The streaming device 200 and the analysis device 300 have the same components as the first embodiment. The acquisition unit 203 provides peak data, which is stored in file-based format in partition 204a in memory 204. The streaming device 200 processes the peak data and generates a data stream S1 containing data packets S1-Pi. The data packets (S1-Pi) are sent to the network 400 via the network interface 210.

[0058] The analyzer 300 is a separate device and is not connected to the local PCI Express bus 216 of the streaming device 200. It contains a CPU 301, a memory 304, a GPU 305, and a local PCI Express bus 316 and is configured to receive the S1-Pi data packets from the network 400 via a network interface 310. As in the first embodiment, the received S1-Pi data packets are stored in a stream-specific partition of the memory 304a, converted, and then allocated to local memory of the GPU 305 cores. The S1-Pi data packets are processed or analyzed in parallel by the GPU 305 cores.

[0059] The data packets R1-Pi result from the analysis of the corresponding data packets S1-Pi. They are stored in memory 304 and sent as result stream R1 to network 400 via network interface 310. The data packets R1-Pi of result stream R1 are received by the streaming device 200 and can be stored in a stream-specific partition 204b of memory 204. The streaming device can, for example, use the received result stream R1 to generate new data streams by combining result stream R1 with peak data in partition 204b, or to control the mass spectrometric system via control line 12, e.g., for planning the precursor ion varieties for a data-dependent MS2 analysis or for adjusting instrumental parameters such as the fragmentation voltage of a CID cell. The received result data can be used directly by network 400 to control the mass spectrometric system.

[0060] Fig. Figure 1 shows a third embodiment of a device for peak data analysis according to the invention, which is coupled to a mass spectrometric system 100' and includes a streaming device 200, two analysis devices (300, 300') and a network 400.

[0061] As in the first embodiment, the mass spectrometric system 100 can, for example, perform the following functions: Fig.The IMS-q-OTOF system is reproduced. In contrast to the embodiments described above, the acquisition unit 103 is not a component of the streaming device 200, but is integrated into the mass spectrometric system 100'. The acquisition unit 103 is connected to an ion detector 171, which provides a pulsed analog current for ions arriving at the ion detector 171. The acquisition unit 103 includes an analog-to-digital converter for digitizing the pulsed electron current and a processing unit for generating peak data from the digitized current. The peak data consists of a list of ordered triples, each triplet representing a single mass signal from an acquired mass spectrum and containing a mobility-related value (e.g., IMS scan time or spectrum number in the IMS scan), a mass-related value (e.g., time of flight or frequency), and an intensity-related value.The mass spectrometric system 100' transmits the peak data as an instrument stream via a network interface 110 to the network 400. The streaming device 200 retrieves the data packets of the instrument stream and stores them in memory 204. The peak data are forwarded as packets, where a packet can contain, for example, a single triplet, all triplets of a single recorded mass spectrum, or all triplets of a multitude of recorded mass spectra, e.g., all mass spectra recorded during an IMS separation.

[0062] As in the embodiments described above, the streaming device includes a CPU 201 and a memory 204 and controls the mass spectrometric system via control line 202. The streaming device 200 receives the peak data from the network via network interface 210 and stores it in partition 204a of memory 204 in a file-based representation. The streaming device processes the peak data and generates a stream S1 containing many data packets (S1-Pi). The data packets (S1-Pi) are sent to the network 400 via network interface 210.

[0063] The analyzers 300 and 300' each contain a CPU (301, 301'), a memory (304, 304'), and a GPU (305, 305') and can receive data packets (S1-Pi) from the network 400 via the corresponding network interfaces (310, 310'). As in the embodiments above, the received data packets S1-Pi are stored in stream-specific partitions (304a, 304'a) of the memory (304, 304'), converted, and then allocated to local memory of the GPU cores (305, 305'). The S1-Pi data packets are processed or analyzed in parallel by the GPU cores (305, 305').

[0064] When one of the analyzers (300, 300') retrieves a data packet and assigns it to a core of the GPU (305, 305'), a data packet of a feedback stream F1 is generated and distributed to network 400. The analyzers (300, 300') as well as the streaming device 200 receive data packets of the feedback stream F1 from network 400. The feedback stream F1 can help organize the distribution of data packets from the streaming device to multiple analyzers. In addition to the feedback stream, the analyzers (300, 300') can share the results of their analyses using result streams (not shown) over network 400. The streaming device 200 can also receive result streams from the analyzers (300, 300'). The received result streams can be used by the streaming device 200 to control the mass spectrometric system (e.g.,to deselect all precursor peptide ion types from a selection list of a data-dependent analysis relating to a protein identified by one of the analytical devices) and also to combine received result stream data with peak data to generate and send combined streams to be analyzed by the analytical devices.

[0065] The invention is described above with reference to various specific embodiments. It is understood, however, that various aspects or details of the described embodiments can be modified without deviating from the scope of the invention. Furthermore, the features and measures disclosed in connection with different embodiments can be combined as desired, provided this appears practical to a person skilled in the art. Moreover, the above description serves only to illustrate the invention and not to limit the scope of protection, which is defined exclusively by the accompanying claims, taking into account any existing equivalents.

Claims

[1] Device for analyzing peak data generated from mass signals recorded by a mass spectrometric system (100, 100') comprising: a streaming device (200) which includes a first network interface (210) and is configured to (a) generate peak data from the recorded mass signals or to receive peak data generated externally from the recorded mass signals, (b) group the peak data into independently processable data packets relating to different processing tasks, and (c) distribute the data packets in different task-specific streams over the first network interface (210) to a network (400); and at least one analysis device (300) which includes a second network interface (310) and is configured to (a) retrieve the data packets of the various task-specific streams from the network (400) via the second network interface (310), (b) perform the processing tasks on the retrieved data packets to generate result data, (c) package the result data into result data packets, and (d) distribute the result data packets to the network (400) via the second network interface (310). [2] Device according to claim 1, characterized by , that the peak data are a series of tuples, where each tuple represents a single mass signal. [3] Device according to claim 1 or claim 2, characterized by, that the at least one analysis device (300) contains a plurality of processing units, each of which is configured to perform one or more processing tasks simultaneously on different data packets. [4] Device according to claim 3, characterized by , that the at least one analysis device (300) contains a main processor (CPU) (301), a global memory (304) and a graphics processing unit (GPU) (305) and the CPU (301) is configured to store retrieved data packets of the various task-specific streams in the global memory (304), to convert the data packets into a GPU-compatible format and to forward the converted data packets to the GPU cores, which simultaneously perform the respective processing task on the converted data packets. [5] Device according to any one of claims 1 to 4, characterized by, that the device contains a multitude of analysis devices (300, 300') configured to perform the processing tasks simultaneously on different data packets. [6] Device according to claim 5, characterized by , that each data packet is distributed with a header containing an identification key and / or information regarding the analyzer (300, 300') that is to retrieve and process the data packet. [7] Device according to claim 5 or claim 6, characterized by , that the analyzers (300, 300') remain configured to retrieve result data packages from the other analyzers (300, 300'), and characterized by , that the result data of an analyzer (300, 300') contain information that a specific data packet is being processed by the analyzer (300, 300'). [8] Device according to any one of claims 1 to 7, characterized by, that each data packet is distributed with a header containing information regarding the respective processing task. [9] Device according to any one of claims 1 to 8, characterized by , that the intersection set between a first data packet of a first task-specific stream and a second data packet of a different task-specific stream is not empty, i.e., that a single tuple of the peak data exists in different task-specific streams. [10] Device according to any one of claims 1 to 9, characterized by , that the streaming device (200) is configured to generate each data packet of a task-specific stream immediately after the peak data necessary for the data packet is available, so that the data packets of the task-specific stream are distributed to the network (400) in real time. [11] Device according to any one of claims 1 to 10, characterized by, that the streaming device (200) includes a recording unit (203) which is connected to a local computer bus (216) of the streaming device (200) and an ion detector (171) of the mass spectrometric system (100) and is configured to generate the peak data from the mass signals detected by the ion detector (171). [12] Device according to claim 11, characterized by , that the ion detector (171) generates a pulsed electron current, wherein said ion detector (171) preferably includes a secondary electron multiplier and the recording unit (203) includes an analog-to-digital converter for digitizing the pulsed electron current and a processing unit to generate the peak data from the digitized signal, for example by a real-time peak search algorithm. [13] Device according to any one of claims 1 to 10, characterized by, that the streaming device (200) is connected to a recording unit (103) of the mass spectrometric system (100) via the network (400) or an additional data link, wherein said recording unit (103) is connected to and configured with an ion detector (171) of the mass spectrometric system (100) to (a) generate peak data from the mass signals detected by the ion detector (171) and (b) forward the peak data to the streaming device (200) via the network interface (110) or the additional data link. [14] Device according to any one of claims 1 to 13, characterized by , that the streaming device (200) remains configured to retrieve the result data packets from the network (400) and organize them according to a predetermined result data protocol. [15] Device according to claim 14, characterized by, that the streaming device (200) is further configured to combine the peak data and the retrieved result data into independently processable data packets relating to an additional processing task, and to distribute the data packets in an additional task-specific stream over the first network interface (210) to a network (400). [16] Device according to claim 14 or claim 15, characterized by , that the streaming device (200) is connected to and configured with the mass spectrometric system (100), the operation of which is to be modified depending on the result data of the retrieved result data packets. [17] Device according to any one of claims 1 to 16, characterized by , that it further includes an additional device configured to retrieve the result data packets from the network (400) and organize them according to a predetermined result data protocol. [18] Device according to claim 17, characterized by , that the additional device is connected to and configured with the mass spectrometric system (100), the operation of which is to be changed depending on the result data of the retrieved result data packages. [19] Device according to any one of claims 1 to 18, characterized by that the network (400) uses an Ethernet protocol. [20] Device according to any one of claims 1 to 19, characterized by that it still contains a local area network (LAN). [21] Device according to any one of claims 1 to 20, characterized by , that each data packet is distributed with a header containing operating parameters of the mass spectrometric system (100) and / or acquisition times of the mass signals represented in the data packet, relating to retention times of corresponding analytes eluted from a separation device coupled to the mass spectrometric system (100). [22] Device according to any one of claims 1 to 21, characterized by , that each tuple of peak data is a triple containing a mobility-related value, a mass-related value and an intensity-related value and represents a single mass signal recorded by the mass spectrometric system (100) comprising a mobility separator (144) and a mass analyzer (170). [23] Device according to any one of claims 1 to 20, characterized by , that each tuple of peak data is a quadruple containing two coordinates of a position on a sample, a mass-related value and an intensity-related value, and represents a single mass signal that is recorded by the mass spectrometric system (100) which includes an ion source (171) configured to generate ions from different positions on the sample (e.g. a tissue section) and a mass analyzer (170). [24] Device according to any one of claims 1 to 20, characterized by , that each tuple of peak data is a quintuple containing two coordinates of a position on a sample, a mobility-related value, a mass-related value and an intensity-related value, and represents a single mass signal recorded by the mass spectrometric system (100) which includes an ion source (171) configured to generate ions from different positions on the sample (e.g. a tissue section), a mobility separator (144) and a mass analyzer (170). [25] Device according to any one of claims 1 to 20, characterized by, that mass signals are recorded in an MS1 ​​mode of the mass spectrometric system (100) which includes a mobility separator (144) and a mass analyzer (170), and the processing tasks relate to the identification of precursor ions in a mass-mobility map, one axis of which shows the ion mobility, while an axis perpendicular to it shows the charge-related mass. [26] Device according to any one of claims 1 to 20, characterized by , that mass signals are recorded in an MS2 mode of the mass spectrometric system (100) which includes a mobility separator (144), a fragmentation cell (160) and a mass analyzer (170), and the processing tasks relate to the identification of an ion species using the mass signals of the recorded MS2 mass spectrum. [27] Device according to any one of claims 1 to 20, characterized by, that mass signals are recorded in an MS2 mode of the mass spectrometric system (100) which includes a mobility separator (144), a fragmentation cell (160) and a mass analyzer (170), and the processing tasks relate to the determination of the presence of a marker ion or neutral loss in the recorded MS2 mass spectrum.

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