A method, apparatus, device, and medium for identifying microorganisms

Abstract

The application discloses a kind of microbial identification method, device, equipment and medium, it is applied to preset microorganism mass spectrometer in microbial analysis technical field, comprising: standard sample is sampled and identified, to obtain standard identification result;Determine current sampling position, and sample is sampled to the sample to be detected using each preset laser energy, to obtain current identification mass spectrum, and the number of current sampled positions is counted;Current identification mass spectrum is identified to obtain current comparison identification result;Current comparison identification result is compared with standard identification result, if it meets preset condition, update current mark number;Based on current mark number and current sampled position number determine whether the sample to be detected is interpreted as positive, then determine new current sampling position, and jump to the step of using each preset laser energy to sample the sample to be detected, until it meets loop end condition.This can improve the speed and accuracy of microbial identification.

Description

Technical Field

[0001] This invention relates to the field of microbial analysis technology, and in particular to a method, apparatus, equipment and medium for microbial identification. Background Technology

[0002] In clinical or non-clinical testing, microbial mass spectrometry is sometimes required to detect microbial growth. For example, in phenotypic drug susceptibility testing, the same microorganism needs to be spotted onto sample spots with different concentrations of antibiotics, and the detection of the corresponding microorganism is required at each sample spot. In this case, a well-defined method for interpreting microbial growth is needed to complete the relevant tests and provide positive or negative results, where a positive result indicates growth, and a negative result indicates no growth or absence of the microorganism.

[0003] Currently, two methods are commonly used to interpret microbial mass spectra:

[0004] The first method involves detecting the presence of a certain number of mass spectral peaks in the microbial mass spectrometer, or determining the peak height, peak area, signal-to-noise ratio, and other attributes. A positive result is indicated when a certain number of mass spectral peaks are detected and the signal-to-noise ratio reaches a certain value; otherwise, a negative result is indicated. However, this method has several drawbacks: it requires high-level sample pretreatment, which can lead to false negatives due to poor peak elution; it is also highly dependent on the instrument's condition, as instrument degradation can result in poor peak elution and false negatives; and it suffers from poor compatibility with different microbial strains, as the protein fingerprints of different microorganisms vary significantly, necessitating the setting of different thresholds for different microorganisms as judgment criteria.

[0005] The second method involves training the microbial mass spectrometer using artificial intelligence methods such as neural network models to construct a binary classifier, which is then used to interpret the microbial mass spectrometer data. However, this method also has several shortcomings: it requires a large amount of positive or negative data for training, and as the number of bacterial species to be detected increases, the amount of data that needs to be collected and trained will increase linearly or even geometrically; when the sample is contaminated, especially when the contaminating microorganisms dominate, the detection accuracy decreases significantly; and the more complex the artificial intelligence method, such as the neural network, the stronger its uninterpretability, making troubleshooting difficult.

[0006] As can be seen from the above, how to improve the speed and accuracy of microbial identification in the process of microbial identification is an urgent problem to be solved. Summary of the Invention

[0007] In view of this, the purpose of this invention is to provide a method, apparatus, device, and medium for microbial identification, which can determine whether a sample to be tested is positive based on the current number of positive markers and the current number of sampled locations, thereby improving the speed of microbial identification and enhancing the accuracy of the results obtained. The specific solution is as follows:

[0008] In a first aspect, this application provides a method for microbial identification, applied to a pre-set microbial mass spectrometer, comprising:

[0009] The standard sample placed in the target sample is sampled and identified to obtain the standard identification result corresponding to the standard mass spectrum of the standard sample;

[0010] The current sampling position in the target sample is determined, and the sample to be detected at the current sampling position is sampled using each preset laser energy to obtain the corresponding current mass spectrum to be identified, and the corresponding number of current sampling positions is counted.

[0011] The current mass spectrum to be identified is analyzed to obtain the corresponding current comparison identification results;

[0012] The current identification result to be compared is compared with the standard identification result, and the current number of positive markers is updated when the current comparison result meets the preset conditions;

[0013] Based on the current number of positive markers and the current number of sampled positions, determine whether to interpret the sample to be tested at the current sampling position as positive. Then, take the next sampling position in the target sample target as the new current sampling position and jump to the step of sampling the sample to be tested at the current sampling position using each preset laser energy until the preset loop end condition is met.

[0014] Optionally, the step of sampling and identifying the standard sample placed in the target sample to obtain a standard identification result corresponding to the standard mass spectrum of the standard sample includes:

[0015] The standard sample placed in the target sample is sampled to obtain a standard mass spectrum corresponding to the standard sample, and it is determined whether the standard mass spectrum meets the first index; if the standard mass spectrum does not meet the first index, the microbial identification process is terminated.

[0016] If the standard mass spectrum meets the first index, the standard mass spectrum is identified, and it is determined whether the obtained standard identification result meets the preset confidence condition.

[0017] If the standard identification result meets the preset confidence level, the standard identification result corresponding to the standard sample is recorded; if the standard identification result does not meet the preset confidence level, the microbial identification process is exited.

[0018] Optionally, after determining the current sampling position in the target sample target, sampling the sample to be detected at the current sampling position using preset laser energies to obtain the corresponding current mass spectrum to be identified, and counting the corresponding number of currently sampled positions, the method further includes:

[0019] Count the current preset energy sequence number and determine whether the current preset energy sequence number is less than the total number of laser energies;

[0020] If the current preset energy number is less than the total number of laser energies, then an operation is triggered to sample the sample to be detected at the current sampling position using another preset laser energy.

[0021] If the current preset energy sequence number is not less than the total number of laser energies, then the next sampling position in the target sample target is taken as the new current sampling position, and the process jumps to the step of sampling the sample to be tested at the current sampling position using each preset laser energy.

[0022] Optionally, the step of comparing the current identification result to be compared with the standard identification result, and updating the current number of positive markers when the current comparison result meets a preset condition, includes:

[0023] The current identification result to be compared is compared with the standard identification result to obtain the current comparison result;

[0024] If the comparison result indicates that the identification result to be compared is consistent with the standard identification result, then it is determined whether the identification result to be compared meets the preset confidence condition;

[0025] If the comparison and identification results meet the preset confidence conditions, then the current number of positive markers corresponding to the sample to be tested is updated.

[0026] Optionally, the step of comparing the current identification result to be compared with the standard identification result, and updating the current number of positive markers when the current comparison result meets a preset condition, includes:

[0027] According to the screening order of the bacterial species identification scores from largest to smallest in the identification results to be compared, a target number of bacterial species are determined from each bacterial species corresponding to the sample to be tested, and it is determined whether there are any bacterial species among the target number of bacterial species that are consistent with the standard identification results;

[0028] If there is a strain among the target number of strains that is consistent with the standard identification result, then it is determined whether the strain identification score corresponding to the strain meets the preset confidence condition. If the strain identification score corresponding to the strain meets the preset confidence condition, then the operation of updating the current number of positive markers is triggered.

[0029] Optionally, determining whether to interpret the sample to be tested at the current sampling location as positive based on the current number of positive markers and the current number of sampled locations includes:

[0030] Determine whether the current number of positive markers is equal to the current number of positive targets. If the current number of positive markers is equal to the current number of positive targets, then the sample to be tested is identified as positive, and the microbial identification process is exited.

[0031] If the current number of positive markers is not equal to the current number of positive targets, then it is determined whether the current number of sampled locations is greater than the upper limit of the sampling location. If the current number of sampled locations is greater than the upper limit of the sampling location, then the sample to be tested is interpreted as negative and the microbial identification process is exited.

[0032] Optionally, after determining whether to interpret the sample to be tested at the current sampling location as positive based on the current number of positive markers and the current number of sampled locations, the method further includes:

[0033] The target sample is scanned to determine whether there are any undetected samples in the target sample; if there are no undetected samples in the target sample, the microbial identification process is terminated.

[0034] If there is an undetected sample in the target sample target, the operation of taking the next sampling position in the target sample target as the new current sampling position is triggered.

[0035] Secondly, this application provides a microbial identification device for use in a pre-set microbial mass spectrometer, comprising:

[0036] The identification result acquisition module is used to sample and identify the standard sample placed in the target sample to obtain the standard identification result corresponding to the standard mass spectrum of the standard sample.

[0037] The sampling location determination module is used to determine the current sampling location in the target sample target, and to sample the sample to be detected at the current sampling location using each preset laser energy to obtain the corresponding current mass spectrum to be identified, and to count the corresponding number of current sampling locations.

[0038] The mass spectrum identification module is used to identify the current mass spectrum to be identified in order to obtain the corresponding current comparison identification results;

[0039] The marker count update module is used to compare the current identification result to be compared with the standard identification result, and update the current positive marker count when the current comparison result meets the preset conditions;

[0040] The sample interpretation module is used to determine whether to interpret the sample to be tested at the current sampling position as positive based on the current number of positive markers and the current number of sampled positions. Then, it takes the next sampling position in the target sample target as the new current sampling position and jumps to the step of sampling the sample to be tested at the current sampling position using preset laser energies until the preset loop end condition is met.

[0041] Thirdly, this application provides an electronic device, comprising:

[0042] Memory, used to store computer programs;

[0043] A processor is used to execute the computer program to implement the aforementioned microbial identification method.

[0044] Fourthly, this application provides a computer-readable storage medium for storing a computer program, wherein the computer program, when executed by a processor, implements the aforementioned microbial identification method.

[0045] As can be seen from the above, before performing microbial identification, this application needs to sample and identify the standard sample placed in the target sample target to obtain the standard identification result corresponding to the standard mass spectrum of the standard sample; determine the current sampling position in the target sample target, and use each preset laser energy to sample the sample to be tested at the current sampling position to obtain the corresponding current mass spectrum to be identified, and count the corresponding current sampling positions; identify the current mass spectrum to be identified to obtain the corresponding current comparison identification result; compare the current comparison identification result with the standard identification result, and update the current positive label count when the current comparison result meets the preset conditions; determine whether to interpret the sample to be tested at the current sampling position as positive based on the current positive label count and the current sampling position count, and then take the next sampling position in the target sample target as the new current sampling position, and jump to the step of sampling the sample to be tested at the current sampling position using each preset laser energy, until the preset cycle end condition is met. Therefore, this application identifies a standard sample to obtain a standard identification result, samples the current sampling position using different laser energies, identifies the resulting mass spectrum to be identified, and updates the number of currently sampled positions. Subsequently, the identification result obtained from the mass spectrum to be identified is compared with the standard identification result to obtain a comparison result. Then, it is determined whether the comparison result meets a first preset condition; if so, the current number of positive markers is updated. Finally, based on the current number of positive markers and the current number of sampled positions, it is determined whether the sample to be tested is interpreted as positive. Then, the next sampling position in the target sample is taken as the new current sampling position, and the process jumps to the step of sampling the sample to be tested at the current sampling position using preset laser energies, until the preset cycle termination condition is met. This improves the speed of microbial identification and the accuracy of the results, thereby enhancing the user experience. Attached Figure Description

[0046] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0047] Figure 1 This is a flowchart of a microbial identification method disclosed in this application;

[0048] Figure 2 This is a schematic diagram of uneven crystal distribution in a sample disclosed in this application;

[0049] Figure 3 This is a schematic diagram of a microbial protein fingerprint.

[0050] Figure 4 This is a schematic diagram of a sample target for microbial mass spectrometry.

[0051] Figure 5 This is a schematic diagram of the main process for microbial identification disclosed in this application;

[0052] Figure 6 This is a structural flowchart of a microbial identification device disclosed in this application;

[0053] Figure 7 This is a structural diagram of an electronic device disclosed in this application. Detailed Implementation

[0054] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0055] In clinical or non-clinical testing, microbial mass spectrometry is sometimes required to detect microbial growth. For example, in phenotypic drug susceptibility testing, the same microorganism needs to be spotted onto sample spots with different concentrations of antibiotics, and the detection of the corresponding microorganism is required at each sample spot. In this case, a clear method for interpreting microbial growth is needed to complete the relevant tests and provide positive or negative results, where a positive result indicates growth, and a negative result indicates no growth or absence. Therefore, this application provides a microbial identification method that can determine whether a sample is positive based on the current number of positive markers and the current number of sampling locations, thereby improving the speed of microbial identification.

[0056] See Figure 1 As shown, this embodiment of the invention discloses a method for identifying microorganisms, applied to a pre-set microbial mass spectrometer, comprising:

[0057] Step S11: Sample and identify the standard sample placed in the target sample to obtain the standard identification result corresponding to the standard mass spectrum of the standard sample.

[0058] Microbial mass spectrometry is a widely used instrument for microbial identification in both clinical and non-clinical testing. In one specific embodiment, microbial mass spectrometry uses MALDI-TOF (Matrix Assisted Laser Desorption / Ionization Time-of-Flight Mass Spectrometry) to acquire protein fingerprints of microorganisms. After obtaining the protein fingerprints, they are compared with all known microbial protein fingerprints stored in a microbial mass spectrometry database to obtain the microbial mass spectrometry identification result. This application embodiment allows identification of the specific microbial species based on the microbial mass spectrometry identification result. It is worth noting that the microbial mass spectrometry database can be reused during microbial identification. In one specific embodiment, the microbial mass spectrometry database contains 4000-5000 microbial species, which can meet the needs of most application scenarios.

[0059] In this embodiment, before sampling and identifying the sample to be tested, a control point, i.e., a standard sample, needs to be pre-set. The standard sample placed in the target sample target is then sampled and identified to obtain a standard identification result corresponding to the standard mass spectrum of the standard sample, so that it can be compared with the identification result of the sample to be tested later. Specifically, the sampling and identification of the standard sample placed in the target sample target to obtain a standard identification result corresponding to the standard mass spectrum of the standard sample may include: sampling the standard sample placed in the target sample target to obtain a standard mass spectrum corresponding to the standard sample, and determining whether the standard mass spectrum meets a first indicator; if the standard mass spectrum does not meet the first indicator, the microbial identification process is exited; if the standard mass spectrum meets the first indicator, the standard mass spectrum is identified, and it is determined whether the obtained standard identification result meets a preset confidence condition; if the standard identification result meets the preset confidence condition, the standard identification result corresponding to the standard sample is recorded; if the standard identification result does not meet the preset confidence condition, the microbial identification process is exited.

[0060] Step S12: Determine the current sampling position in the target sample target, and use each preset laser energy to sample the sample to be detected at the current sampling position to obtain the corresponding current mass spectrum to be identified, and count the corresponding number of current sampling positions.

[0061] It is worth mentioning that, in one specific implementation, because different types of microorganisms require different laser energies, when microbial mass spectrometry is sampled using lasers, adverse effects may occur, such as weak detection signals or distorted mass spectrometry signals due to poor crystallization at the sampling location or incompatible laser energy, resulting in peak differences in the mass spectrometry and ultimately false negatives in the detection results. A schematic diagram illustrating uneven sample crystal distribution is shown below. Figure 2 As shown, located Figure 2The red arrow on the left half indicates the area where no sample crystals appeared, while Figure 2 The red arrow on the right half indicates that there is sample crystallization, meaning that there is a problem with uneven crystallization.

[0062] In another specific implementation, increasing the number of samplings and laser variations within the target site can ensure the acquisition of effective sample signals. However, this significantly reduces the detection speed of the microbial mass spectrometer. For example, the number of samplings is the product of the number of sampling locations and the type of laser energy, resulting in a geometric increase in the number of samplings. Furthermore, there are scenarios where the corresponding sample microorganism is non-growing—i.e., a true negative result—causing the microbial mass spectrometer itself to be unable to acquire an effective mass spectrometry signal. In such scenarios, it is also necessary to quickly interpret the negative result of the sample.

[0063] Among them, mass spectrometry can be a microbial protein fingerprint. For example... Figure 3 As shown, Figure 3 This is essentially a microbial protein fingerprint, where the horizontal axis represents the mass-to-charge ratio and the vertical axis represents ionic intensity (i.e., ionic content). Each mass spectral peak represents a protein with a specific mass-to-charge ratio and its corresponding abundance. It's worth noting that the protein fingerprint of each bacterial species is theoretically different. Furthermore, a mass spectrometry database contains known microbial protein fingerprints, and its richness directly determines the types of microorganisms that can be detected by mass spectrometry. The larger the mass spectrometry database, the more types of microorganisms the mass spectrometer can detect.

[0064] It is worth noting that because microbial mass spectrometers are highly dependent on the mass spectrometry detection signal, the identification results will also be inaccurate when the mass spectrometry detection signal is inaccurate. Furthermore, poor sample pretreatment or instrument condition can also lead to incorrect interpretation of the microorganisms being tested, thus easily resulting in false negatives.

[0065] Furthermore, when adding a new species to be tested, it should not require a large amount of work to readjust the method or model; or, when the sample to be tested is contaminated by other microorganisms, for example, in the embodiments of this application, the species to be tested and interpreted is bacteria A, but because it contaminates bacteria B and B grows effectively while A does not grow, the interpretation result may be a false positive; furthermore, when the sample to be tested has poor crystallization, or the microorganisms to be tested are different, or the sample to be tested itself is negative, it is easy to obtain a false negative result, or it may lead to a significant increase in the time required for microbial testing.

[0066] Therefore, in this embodiment of the application, when using a microbial mass spectrometer to interpret the growth of microorganisms, a standard sample point of normal growth needs to be prepared in the target sample target first, to serve as a control point for subsequent microbial identification. Subsequently, this standard sample point needs to be sampled and identified, and then the sample to be tested is sampled and identified multiple times at different sampling locations. In one specific embodiment, the sample target of the microbial mass spectrometer is as follows: Figure 4 As shown.

[0067] In this embodiment, when testing the sample, different laser energies can be used to sample the same sampling location, and the mass spectrum after sampling can be identified. It is worth noting that this embodiment does not impose quality requirements on the mass spectrum itself, but directly performs identification. This addresses the issues of excessively high mass spectrum quality requirements, conflicting negative results, and sample contamination, which can lead to abnormal mass spectrum peaks and errors in microbial identification results. Specifically, after determining the current sampling position in the target sample target, sampling the sample to be tested at the current sampling position using each preset laser energy to obtain the corresponding current mass spectrum to be identified, and counting the corresponding number of currently sampled positions, the method may further include: counting the current preset energy number and determining whether the current preset energy number is less than the total number of laser energies; if the current preset energy number is less than the total number of laser energies, then triggering the operation of sampling the sample to be tested at the current sampling position using another preset laser energy; if the current preset energy number is not less than the total number of laser energies, then taking the next sampling position in the target sample target as the new current sampling position, and jumping to the step of sampling the sample to be tested at the current sampling position using each preset laser energy.

[0068] Step S13: Identify the current mass spectrum to be identified to obtain the corresponding current comparison identification results.

[0069] In this embodiment, after obtaining several current mass spectra to be identified by sampling the sample to be tested using different preset laser energies, it is necessary to identify the several current mass spectra to be identified in order to obtain several current comparison identification results corresponding to the several current mass spectra to be identified, so that the current comparison identification results can be compared with the standard identification results in the future.

[0070] Step S14: Compare the current identification result to be compared with the standard identification result, and update the current number of positive markers when the current comparison result meets the preset conditions.

[0071] It is worth mentioning that if the relative content of contaminating bacteria in the sample to be tested is high, or if the microorganism to be tested does not grow in the sample, the identification result obtained from the identification of the sample to be tested can be compared with the standard identification result. If they are different, the sample to be tested is interpreted as negative. If the relative content of contaminating bacteria in the sample to be tested is low, so that the mass spectrum peaks in the mass spectrum obtained after sampling are not significant, the sample to be tested can still be identified, and it does not affect the identification result. This can solve the problems of crystallization of the sample to be tested and the different laser energies adapted to different microorganisms, and ensures the detection speed while reducing the probability of false negative results.

[0072] In one specific implementation, comparing the current identification result to be compared with the standard identification result, and updating the current positive marker count when the current comparison result meets a preset condition, may include: comparing the current identification result to be compared with the standard identification result to obtain a current comparison result; if the comparison result indicates that the identification result to be compared is consistent with the standard identification result, then determining whether the identification result to be compared meets a preset confidence condition; if the identification result to be compared meets the preset confidence condition, then updating the current positive marker count corresponding to the sample to be tested. That is, if sampling and identification of the sample point to be tested yields a reliable identification result identical to that of the standard sample point, then the sample to be tested can be determined to be positive; if multiple sampling and identification of the sample point to be tested fail to yield a reliable identification result identical to that of the sample point to be tested, then the sample to be tested can be determined to be negative.

[0073] In another specific implementation, the step of comparing the current identification result to be compared with the standard identification result and updating the current number of positive markers when the current comparison result meets a preset condition may include: determining a target number of bacterial species from each bacterial species corresponding to the sample to be tested according to the screening order of bacterial species identification scores from largest to smallest in the identification results to be compared, and determining whether there are any bacterial species consistent with the standard identification result among the target number of bacterial species; if there are bacterial species consistent with the standard identification result among the target number of bacterial species, then determining whether the bacterial species identification score corresponding to the bacterial species meets a preset confidence condition; if the bacterial species identification score corresponding to the bacterial species meets the preset confidence condition, then triggering the operation of updating the current number of positive markers.

[0074] Step S15: Based on the current number of positive markers and the current number of sampled positions, determine whether to interpret the sample to be tested at the current sampling position as positive. Then, take the next sampling position in the target sample target as the new current sampling position and jump to the step of sampling the sample to be tested at the current sampling position using each preset laser energy until the preset loop end condition is met.

[0075] In this embodiment, after obtaining the updated current positive marker count and the current number of sampled locations, this application embodiment needs to compare the updated current positive marker count and the current number of sampled locations with the current positive target number and the upper limit of the sampling location. Specifically, determining whether to interpret the sample to be tested at the current sampling location as positive based on the current positive marker count and the current number of sampled locations may include: determining whether the current positive marker count is equal to the current positive target number; if the current positive marker count is equal to the current positive target number, then the sample to be tested is interpreted as positive, and the microbial identification process is exited; if the current positive marker count is not equal to the current positive target number, then determining whether the current number of sampled locations is greater than the upper limit of the sampling location; if the current number of sampled locations is greater than the upper limit of the sampling location, then the sample to be tested is interpreted as negative, and the microbial identification process is exited.

[0076] It is worth mentioning that after interpreting the sample to be tested at the current sampling location, the target sample target needs to be scanned to determine whether there are any undetected samples in the target sample target. Specifically, after determining whether to interpret the sample to be tested at the current sampling location as positive based on the current number of positive markers and the current number of sampling locations, the process may further include: scanning the target sample target to determine whether there are any undetected samples in the target sample target; if there are no undetected samples in the target sample target, the microbial identification process is exited; if there are undetected samples in the target sample target, the operation of taking the next sampling location in the target sample target as the new current sampling location is triggered.

[0077] It is worth mentioning that, in this application embodiment, identification can also be performed without directly using microbial protein fingerprinting. Instead, other methods can be used to establish a database of the original microbial mass spectra, such as a microbial positive interpretation detection library. This allows for the analysis and comparison of the standard mass spectra corresponding to the standard samples with the comparison mass spectra corresponding to the samples to be tested, thereby enabling a positive interpretation for the samples to be tested. Furthermore, multiple samplings of each sample to be tested can be performed, and several mass spectra to be identified can be identified uniformly.

[0078] As can be seen from the above, before performing microbial identification, this embodiment requires sampling and identifying a standard sample placed in the target sample target to obtain a standard identification result corresponding to the standard mass spectrum of the standard sample; determining the current sampling position in the target sample target, and sampling the sample to be tested at the current sampling position using preset laser energies to obtain the corresponding current mass spectrum to be identified, and counting the corresponding number of current sampling positions; identifying the current mass spectrum to be identified to obtain the corresponding current comparison identification result; comparing the current comparison identification result with the standard identification result, and updating the current positive marker count when the current comparison result meets preset conditions; determining whether to interpret the sample to be tested at the current sampling position as positive based on the current positive marker count and the current number of sampling positions, and then taking the next sampling position in the target sample target as the new current sampling position, and jumping to the step of sampling the sample to be tested at the current sampling position using preset laser energies, until the preset cycle termination condition is met. This improves the speed of microbial identification and the accuracy of the results obtained, thereby enhancing the user experience.

[0079] Further, see Figure 5 As shown in the figure, an embodiment of the present invention discloses a method for microbial identification, comprising:

[0080] In this embodiment, the main process for microbial identification is as follows:

[0081] First, the microorganism to be detected is added to the sample point of the target sample, and a standard sample that can grow normally is added to other sample points in the target sample as a positive control point;

[0082] Next, the standard sample in the target sample is sampled using a pre-set microbial mass spectrometer, and the following sub-steps are performed:

[0083] First sub-step: If the mass spectrum obtained after sampling the standard sample fails to meet the indicators, such as the peak intensity, signal-to-noise ratio, resolution, and number of peaks in the mass spectrum not reaching the preset indicators, then the microbial detection process is determined to have an abnormality and the entire microbial detection process is terminated; if the peak intensity, signal-to-noise ratio, resolution, and number of peaks in the mass spectrum meet the preset indicators, then proceed to the second sub-step.

[0084] The second sub-step involves identifying the standard mass spectrum corresponding to the standard sample in the target sample. If the identification result is unreliable, it is worth mentioning that the preset microbial mass spectrometer will give a score based on the obtained identification result. In this embodiment, the reliability of the obtained identification result can be judged by the above score. If it is unreliable, it is determined that the microbial detection process has an abnormality and the microbial detection process is terminated. If the identification result is reliable, the process proceeds to the third sub-step.

[0085] The third sub-step: Record the standard identification results corresponding to the standard samples. The standard identification results include the species identification scores corresponding to each species, and are arranged in descending order according to the species identification scores.

[0086] In this embodiment, after obtaining the standard identification results, the sample to be tested needs to be sampled and identified. The steps for detecting the sample to be tested within the target sample target are as follows:

[0087] The first step: Select the first sample to be tested in the target sample target, and set a current positive marker number n=0, a current positive target number d, a current sampled position number m=0, and a maximum sampling position value max for the above sample to be tested;

[0088] The second step: Randomly select a sampling location from the locations of the sample to be tested, such as the center of the sample point. Each time, the selected sampling location will be different. After sampling, increment the count of sampling locations by one, i.e., m = m + 1. Subsequently, use different preset laser energies to sample the location multiple times, for example, preset laser energies of 55%, 45%, and 35%. After obtaining several mass spectra, these mass spectra need to be identified.

[0089] It is worth mentioning that, in one specific implementation, if the obtained identification result to be compared is the same as the standard identification result and the credibility determined by the identification score meets the preset credibility requirement, for example, if the full score is 10 points and the obtained identification score is not less than 6 points, then the obtained identification score is considered credible, and the current number of positive markers is incremented by one, that is, n=n+1.

[0090] In another specific implementation, if the top k results of the comparison identification show the same bacterial species as the standard control point and the confidence level determined by the identification score meets the preset confidence level requirement, then the obtained identification score is considered reliable, and the current number of positive markers is incremented by one; where k is a preset target number, which can be set based on the user's own needs. It is worth mentioning that after the above operations are completed, the third step can be performed.

[0091] The third step: When the current number of positive markers equals the current number of positive targets, the sample to be tested is interpreted as positive, and the microbial testing process ends; otherwise, proceed to the fourth step.

[0092] The fourth step: If the number of currently sampled locations is greater than the upper limit of the sampling locations, the sample to be tested will be interpreted as negative and the microbial testing process will end; otherwise, the step of arbitrarily selecting a sampling location from the locations of the sample to be tested will be triggered.

[0093] Fifth step: Repeat the third step until the testing process for all samples to be tested is completed.

[0094] As can be seen from the above, before performing microbial identification, this embodiment requires sampling and identifying a standard sample placed in the target sample target to obtain a standard identification result corresponding to the standard mass spectrum of the standard sample; determining the current sampling position in the target sample target, and sampling the sample to be tested at the current sampling position using preset laser energies to obtain the corresponding current mass spectrum to be identified, and counting the corresponding number of current sampling positions; identifying the current mass spectrum to be identified to obtain the corresponding current comparison identification result; comparing the current comparison identification result with the standard identification result, and updating the current positive marker count when the current comparison result meets preset conditions; determining whether to interpret the sample to be tested at the current sampling position as positive based on the current positive marker count and the current number of sampling positions, and then taking the next sampling position in the target sample target as the new current sampling position, and jumping to the step of sampling the sample to be tested at the current sampling position using preset laser energies, until the preset cycle termination condition is met. This improves the speed of microbial identification and the accuracy of the results obtained, thereby enhancing the user experience.

[0095] Accordingly, see Figure 6 As shown, this application also provides a microbial identification device, applied to a pre-set microbial mass spectrometer, comprising:

[0096] The identification result acquisition module 11 is used to sample and identify the standard sample placed in the target sample to obtain the standard identification result corresponding to the standard mass spectrum of the standard sample.

[0097] The sampling position determination module 12 is used to determine the current sampling position in the target sample target, and to sample the sample to be detected at the current sampling position using each preset laser energy to obtain the corresponding current mass spectrum to be identified, and to count the corresponding number of current sampling positions.

[0098] The mass spectrum identification module 13 is used to identify the current mass spectrum to be identified in order to obtain the corresponding current identification result to be compared.

[0099] The marker count update module 14 is used to compare the current identification result to be compared with the standard identification result, and update the current positive marker count when the current comparison result meets the preset conditions;

[0100] The sample interpretation module 15 is used to determine whether to interpret the sample to be tested at the current sampling position as positive based on the current number of positive markers and the current number of sampled positions. Then, it takes the next sampling position in the target sample target as the new current sampling position and jumps to the step of sampling the sample to be tested at the current sampling position using each preset laser energy until the preset loop end condition is met.

[0101] As can be seen from the above, before performing microbial identification, this application needs to sample and identify the standard sample placed in the target sample target to obtain the standard identification result corresponding to the standard mass spectrum of the standard sample; determine the current sampling position in the target sample target, and use each preset laser energy to sample the sample to be tested at the current sampling position to obtain the corresponding current mass spectrum to be identified, and count the corresponding current sampling positions; identify the current mass spectrum to be identified to obtain the corresponding current comparison identification result; compare the current comparison identification result with the standard identification result, and update the current positive label count when the current comparison result meets the preset conditions; determine whether to interpret the sample to be tested at the current sampling position as positive based on the current positive label count and the current sampling position count, and then take the next sampling position in the target sample target as the new current sampling position, and jump to the step of sampling the sample to be tested at the current sampling position using each preset laser energy, until the preset cycle end condition is met.

[0102] Therefore, this application identifies a standard sample to obtain a standard identification result, samples the current sampling position using different laser energies, identifies the resulting mass spectrum to be identified, and updates the number of currently sampled positions. Subsequently, the identification result obtained from the mass spectrum to be identified is compared with the standard identification result to obtain a comparison result. Then, it is determined whether the comparison result meets a first preset condition; if so, the current number of positive markers is updated. Finally, based on the current number of positive markers and the current number of sampled positions, it is determined whether the sample to be tested is interpreted as positive. Then, the next sampling position in the target sample is taken as the new current sampling position, and the process jumps to the step of sampling the sample to be tested at the current sampling position using preset laser energies, until the preset cycle termination condition is met. This improves the speed of microbial identification and the accuracy of the results, thereby enhancing the user experience.

[0103] In some specific embodiments, the identification result acquisition module 11 may specifically include:

[0104] The standard mass spectrum acquisition unit is used to sample the standard sample placed in the target sample to obtain the standard mass spectrum corresponding to the standard sample, and to determine whether the standard mass spectrum meets the first index; if the standard mass spectrum does not meet the first index, the microbial identification process is terminated.

[0105] A mass spectrum identification unit is used to identify the standard mass spectrum if the standard mass spectrum meets the first index, and to determine whether the obtained standard identification result meets the preset confidence condition.

[0106] The identification result recording unit is used to record the standard identification result corresponding to the standard sample if the standard identification result meets the preset confidence condition; and to exit the microbial identification process if the standard identification result does not meet the preset confidence condition.

[0107] In some specific embodiments, the microbial identification device may further include:

[0108] An energy sequence number counting unit is used to count the current preset energy sequence number and determine whether the current preset energy sequence number is less than the total amount of laser energy.

[0109] The sample sampling unit is used to trigger an operation of sampling the sample to be detected at the current sampling position using another preset laser energy if the current preset energy number is less than the total number of laser energies.

[0110] The step jump unit is used to, if the current preset energy sequence number is not less than the total number of laser energies, take the next sampling position in the target sample target as the new current sampling position, and jump to the step of sampling the sample to be tested at the current sampling position using each preset laser energy.

[0111] In some specific embodiments, the marker number update module 14 may specifically include:

[0112] The comparison result determination unit is used to compare the current identification result to be compared with the standard identification result to obtain the current comparison result;

[0113] An identification result judgment unit is used to determine whether the identification result to be compared meets a preset credibility condition if the comparison result indicates that the identification result to be compared is consistent with the standard identification result.

[0114] The label number update unit is used to update the current positive label number corresponding to the sample to be tested if the identification result to be compared meets the preset confidence condition.

[0115] In some specific embodiments, the marker number update module 14 may specifically include:

[0116] The microbial species determination unit is used to determine a target number of microbial species from the microbial species corresponding to the sample to be tested according to the screening order of the microbial species identification scores in the identification results to be compared from large to small, and to determine whether there are microbial species among the target number of microbial species that are consistent with the standard identification results.

[0117] The identification score judgment unit is used to determine whether the identification score of the bacterial species corresponding to the target number of bacterial species meets the preset confidence condition if there is a bacterial species that is consistent with the standard identification result. If the identification score of the bacterial species corresponding to the bacterial species meets the preset confidence condition, the operation of updating the current number of positive markers is triggered.

[0118] In some specific embodiments, the sample interpretation module 15 may specifically include:

[0119] The label count determination unit is used to determine whether the current positive label count is equal to the current positive target count. If the current positive label count is equal to the current positive target count, the sample to be tested is identified as positive and the microbial identification process is exited.

[0120] The sampling location number determination unit is used to determine whether the current number of sampled locations is greater than the upper limit of sampling locations if the current number of positive markers is not equal to the current number of positive targets. If the current number of sampled locations is greater than the upper limit of sampling locations, the sample to be tested is interpreted as negative and the microbial identification process is exited.

[0121] In some specific embodiments, the microbial identification device may further include:

[0122] The sample target scanning unit is used to scan the target sample target to determine whether there is an undetected sample to be tested in the target sample target; if there is no undetected sample to be tested in the target sample target, the microbial identification process is terminated.

[0123] The sampling position update unit is used to trigger the operation of taking the next sampling position in the target sample target as the new current sampling position if there is an undetected sample in the target sample target.

[0124] Furthermore, embodiments of this application also disclose an electronic device, Figure 7 This is a structural diagram of an electronic device 20 according to an exemplary embodiment. The content of the diagram should not be construed as limiting the scope of this application. The electronic device 20 may specifically include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25, and a communication bus 26. The memory 22 stores a computer program, which is loaded and executed by the processor 21 to implement the relevant steps in the microbial identification method disclosed in any of the foregoing embodiments. Furthermore, the electronic device 20 in this embodiment may specifically be an electronic computer.

[0125] In this embodiment, the power supply 23 is used to provide operating voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and external devices, and the communication protocol it follows can be any communication protocol applicable to the technical solution of this application, and is not specifically limited here; the input / output interface 25 is used to acquire external input data or output data to the outside world, and its specific interface type can be selected according to specific application needs, and is not specifically limited here.

[0126] In addition, the memory 22, as a carrier for resource storage, can be a read-only memory, random access memory, disk or optical disk, etc. The resources stored thereon can include operating system 221, computer program 222, etc., and the storage method can be temporary storage or permanent storage.

[0127] The operating system 221 is used to manage and control the various hardware devices on the electronic device 20 and the computer program 222, which may be Windows Server, Netware, Unix, Linux, etc. In addition to including a computer program capable of performing the microbial identification method executed by the electronic device 20 as disclosed in any of the foregoing embodiments, the computer program 222 may further include a computer program capable of performing other specific tasks.

[0128] Furthermore, this application also discloses a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, it implements the aforementioned disclosed method for identifying microorganisms. Specific steps of this method can be found in the corresponding content disclosed in the foregoing embodiments, and will not be repeated here.

[0129] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to in the method section.

[0130] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0131] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0132] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0133] The technical solutions provided in this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for identifying microorganisms, characterized in that, Applications in microbial mass spectrometry include: The standard sample placed in the target sample is sampled and identified to obtain the standard identification result corresponding to the standard mass spectrum of the standard sample; The current sampling position in the target sample is determined, and the current sampling position in the sample to be tested is sampled using each preset laser energy to obtain the corresponding current mass spectrum to be identified, and the corresponding number of current sampled positions is counted; wherein, the counting of the corresponding number of current sampled positions includes: after each sampling of the current sampling position in the sample to be tested using all preset laser energy, the number of current sampled positions is incremented by one; The current mass spectrum to be identified is analyzed to obtain the corresponding current comparison identification results; The current identification result to be compared is compared with the standard identification result, and the current positive marker count is updated when the current comparison result meets the preset conditions; the current positive marker count is the cumulative number of times when the current identification result to be compared of the current sample to be tested is consistent with the standard identification result and the confidence of the identification score meets the preset confidence requirement. Based on the current number of positive markers and the current number of sampled positions, determine whether to interpret the sample to be tested as positive. Then, set the sampling position in the next sample to be tested in the target sample target as the new current sampling position, and jump to the step of sampling the current sampling position in the sample to be tested using each preset laser energy until the preset loop end condition is met. The step of determining whether to classify the sample to be tested as positive based on the current number of positive markers and the current number of sampled locations includes: determining whether the current number of positive markers is equal to the current target number of positive markers; if the current number of positive markers is equal to the current target number of positive markers, the sample to be tested is classified as positive, and the current microbial identification process is exited; if the current number of positive markers is not equal to the current target number of positive markers, determining whether the current number of sampled locations is greater than the upper limit of a single sample sampling location; if the current number of sampled locations is greater than the upper limit of a single sample sampling location, the sample to be tested is classified as negative, and the current microbial identification process is exited; the upper limit of a single sample sampling location is the maximum number of sampling locations set based on the sample to be tested; exiting the current microbial identification process means exiting the identification process for the current sample to be tested; the current target number of positive markers is a preset positive classification threshold; The process of determining the current sampling position in the target sample and sampling the current sampling position in the sample to be tested using preset laser energies to obtain the corresponding current mass spectrum to be identified, and counting the corresponding number of currently sampled positions, includes: counting the current preset energy number and determining whether the current preset energy number is less than the total number of laser energies; if the current preset energy number is less than the total number of laser energies, then triggering the operation of sampling the current sampling position in the sample to be tested using another preset laser energy; if the current preset energy number is not less than the total number of laser energies, then setting the next sampling position in the sample to be tested as the new current sampling position, and jumping to the step of sampling the current sampling position in the sample to be tested using each preset laser energy.

2. The microbial identification method according to claim 1, characterized in that, The sampling and identification of the standard sample placed in the target sample to obtain the standard identification result corresponding to the standard mass spectrum of the standard sample includes: The standard sample placed in the target sample is sampled to obtain a standard mass spectrum corresponding to the standard sample, and it is determined whether the standard mass spectrum meets the first index; if the standard mass spectrum does not meet the first index, the overall microbial identification process is terminated. If the standard mass spectrum meets the first index, the standard mass spectrum is identified, and it is determined whether the obtained standard identification result meets the preset confidence condition. If the standard identification result meets the preset confidence level, the standard identification result corresponding to the standard sample is recorded; if the standard identification result does not meet the preset confidence level, the overall microbial identification process is exited.

3. The microbial identification method according to claim 1, characterized in that, The step of comparing the current identification result to be compared with the standard identification result, and updating the current positive marker count when the current comparison result meets preset conditions, includes: The current identification result to be compared is compared with the standard identification result to obtain the current comparison result; If the current comparison result indicates that the current identification result to be compared is consistent with the standard identification result, then it is determined whether the identification result to be compared meets the preset confidence condition; If the comparison and identification results meet the preset confidence conditions, then the current number of positive markers corresponding to the sample to be tested is updated.

4. The microbial identification method according to claim 1, characterized in that, The step of comparing the current identification result to be compared with the standard identification result, and updating the current positive marker count when the current comparison result meets preset conditions, includes: According to the screening order of the bacterial species identification scores from largest to smallest in the current identification results to be compared, a target number of bacterial species are determined from each bacterial species corresponding to the sample to be tested, and it is determined whether there are any bacterial species among the target number of bacterial species that are consistent with the standard identification results; If there is a strain among the target number of strains that is consistent with the standard identification result, then it is determined whether the strain identification score corresponding to the strain meets the preset confidence condition. If the strain identification score corresponding to the strain meets the preset confidence condition, then the operation of updating the current number of positive markers is triggered.

5. The microbial identification method according to any one of claims 1 to 4, characterized in that, After determining whether to interpret the sample to be tested at the current sampling location as positive based on the current number of positive markers and the current number of sampled locations, the method further includes: The target sample is scanned to determine whether there are any undetected samples in the target sample; if there are no undetected samples in the target sample, the overall microbial identification process is terminated. If there is an undetected sample in the target sample target, the operation of setting the sampling position in the next sample to be detected in the target sample target as the new current sampling position is triggered.

6. A microbial identification device, characterized in that, Applications in microbial mass spectrometry include: The identification result acquisition module is used to sample and identify the standard sample placed in the target sample to obtain the standard identification result corresponding to the standard mass spectrum of the standard sample. The sampling location determination module is used to determine the current sampling location in the target sample target, and to sample the current sampling location in the sample to be tested using each preset laser energy to obtain the corresponding current mass spectrum to be identified, and to count the corresponding number of current sampling locations; wherein, the counting of the corresponding number of current sampling locations includes: after each sampling of the current sampling location in the sample to be tested using all preset laser energy, the number of current sampling locations is incremented by one; The mass spectrum identification module is used to identify the current mass spectrum to be identified in order to obtain the corresponding current comparison identification results; The label update module is used to compare the current identification result to be compared with the standard identification result, and update the current positive label count when the current comparison result meets the preset conditions; the current positive label count is the cumulative number of times that the current identification result to be compared of the current sample to be tested is consistent with the standard identification result and the confidence of the identification score meets the preset confidence requirement. The sample interpretation module is used to determine whether to interpret the sample to be tested as positive based on the current number of positive markers and the current number of sampled positions. Then, it sets the sampling position in the next sample to be tested in the target sample target as the new current sampling position and jumps to the step of sampling the current sampling position in the sample to be tested using each preset laser energy until the preset loop end condition is met. The sample interpretation module specifically includes: determining whether the current number of positive markers is equal to the current number of positive targets; if the current number of positive markers is equal to the current number of positive targets, the sample to be tested is interpreted as positive, and the current microbial identification process is exited; if the current number of positive markers is not equal to the current number of positive targets, determining whether the current number of sampled locations is greater than the upper limit of a single sample sampling location; if the current number of sampled locations is greater than the upper limit of a single sample sampling location, the sample to be tested is interpreted as negative, and the current microbial identification process is exited; the upper limit of a single sample sampling location is the maximum number of sampling locations within the sample to be tested, set based on the sample to be tested; exiting the current microbial identification process means exiting the identification process for the current sample to be tested; the current number of positive targets is a preset positive interpretation threshold; Specifically, the microbial identification device is further configured to: count the current preset energy sequence number and determine whether the current preset energy sequence number is less than the total number of laser energies; if the current preset energy sequence number is less than the total number of laser energies, trigger the operation of sampling the current sampling position in the sample to be tested using another preset laser energy; if the current preset energy sequence number is not less than the total number of laser energies, set the next sampling position in the sample to be tested as the new current sampling position, and jump to the step of sampling the current sampling position in the sample to be tested using each preset laser energy.

7. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor for executing the computer program to implement the steps of the microbial identification method as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, Used to store a computer program, wherein the computer program, when executed by a processor, implements the steps of the microbial identification method as described in any one of claims 1 to 5.

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