WO2021203982A1 - Procédé et système basés sur une technologie de séquençage de troisième génération pour détecter des micro-organismes - Google Patents

Procédé et système basés sur une technologie de séquençage de troisième génération pour détecter des micro-organismes Download PDF

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WO2021203982A1
WO2021203982A1 PCT/CN2021/083090 CN2021083090W WO2021203982A1 WO 2021203982 A1 WO2021203982 A1 WO 2021203982A1 CN 2021083090 W CN2021083090 W CN 2021083090W WO 2021203982 A1 WO2021203982 A1 WO 2021203982A1
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detection result
detection
data
preset condition
condition threshold
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夏涵
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西咸新区予果微码生物科技有限公司
予果生物科技（北京）有限公司
予果智造科技(北京)有限公司
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    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6869—Methods for sequencing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/10—File systems; File servers
    • G06F16/16—File or folder operations, e.g. details of user interfaces specifically adapted to file systems
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/10—File systems; File servers
    • G06F16/16—File or folder operations, e.g. details of user interfaces specifically adapted to file systems
    • G06F16/164—File meta data generation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/60—Protecting data
    • G06F21/602—Providing cryptographic facilities or services
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2221/00—Indexing scheme relating to security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F2221/21—Indexing scheme relating to G06F21/00 and subgroups addressing additional information or applications relating to security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F2221/2107—File encryption

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  • the invention relates to the technical field of microbial detection, in particular to a microbial detection method and system based on the third-generation sequencing technology.
  • the third-generation sequencing technology refers to single-molecule sequencing technology. When DNA sequencing, PCR amplification is not required, and each DNA molecule can be individually sequenced.
  • the third-generation sequencing technology is also called de novo sequencing technology, that is, single-molecule real-time DNA sequencing.
  • the third-generation sequencing technology does not require amplification, and directly sequence single-stranded DNA/RNA by directly synthesizing, degrading, and directly sequencing through nanopores, etc., with detection The characteristics of short time and low detection cost.
  • the detection of microorganisms basically uses the plate colony counting method to detect microorganisms; the plate colony counting method is to properly dilute the sample to be tested, the microorganisms in it are fully dispersed into single cells, and a certain amount of diluted sample solution is applied to the plate After culturing, each single cell grows and multiplies to form a colony visible to the naked eye, that is, a single colony should represent a single cell in the original sample; count the number of colonies, and calculate the sample according to its dilution factor and sampling inoculum The number of bacteria in it. It takes 48-72 hours to detect microorganisms by using the plate colony counting method, which makes the detection time consuming longer.
  • the present invention provides a microorganism detection method and system based on third-generation sequencing technology to shorten the time spent on microorganism detection.
  • An embodiment of the present invention provides a microorganism detection method based on third-generation sequencing technology, and the method includes:
  • the step: using third-generation sequencing technology to detect the microbial sample, and obtaining the detection result includes the following steps:
  • the nanopore is constructed with ⁇ -hemolysin, exonuclease is formed on the outer surface of one side of the nanopore, and cyclodextrin is covalently bound to the inner surface of the nanopore as a sensor;
  • a preset voltage is provided on both sides of the lipid bilayer, so that the exonuclease digests single-stranded DNA, a single base falls into the nanopore, and temporarily interacts with the cyclodextrin in the nanopore.
  • the interaction affects the current flowing through the nanopore, and sequencing is achieved according to the residence time, current, and interference amplitude of each base in the cyclodextrin.
  • the preset encryption algorithm includes one or more of asymmetric encryption algorithm, md5 encryption algorithm, and AES encryption algorithm.
  • the step: performing intelligent recognition processing on the detection result, and judging whether the detection result is abnormal includes the following steps:
  • intelligent recognition processing is performed on the detection result, after judging whether the detection result is abnormal, an abnormal warning can be issued after the abnormality is determined, and the following steps are performed:
  • Step A1 Obtain the environmental information during the detection, and determine the height of the detection stimulus line spectrum corresponding to the environmental information;
  • h is the height of the detection stimulus line spectrum
  • e is the natural constant
  • P is the pressure information in the environmental information
  • c is the concentration obtained from the detection of the microbial sample
  • S is the preset environmental expansion coefficient
  • L is the preset Laser gas intensity
  • ⁇ 0 is the propagation speed of light in the current environmental medium
  • Mw is the molecular mass of the microbial sample
  • T is the temperature in the environmental information
  • ⁇ is the propagation speed of light in vacuum
  • Step A2 Determine the adjustment coefficient corresponding to the environmental information
  • fs is the adjustment coefficient corresponding to the environmental information
  • Step A3 Determine the intelligent identification processing result of the microorganism according to the adjustment coefficient and the height of the detected stimulus line spectrum
  • rt is the result of the intelligent identification processing
  • Sf is the area of the microorganism sample to be tested
  • N is the total amount of the microorganism under the preset standard
  • Step A4 Determine whether the total amount of microorganisms in the detection result is greater than the intelligent identification processing result, if it is greater, whether the detection result is abnormal, perform detection and issue an abnormal warning, otherwise continue to perform subsequent processing.
  • a microbial detection system based on third-generation sequencing technology.
  • the system includes: an acquisition module, a detection module, and an intelligent identification module, wherein:
  • the obtaining module is used to obtain microbial samples
  • the detection module is configured to use third-generation sequencing technology to detect the microbial sample acquired by the acquisition module, acquire the detection result, and transmit the detection result to the intelligent identification module;
  • the intelligent identification module is used to perform intelligent identification processing on the detection result transmitted by the detection module, and determine whether the detection result is abnormal.
  • system further includes a storage module
  • the detection module is further configured to transmit the detection result to the storage module;
  • the storage module is configured to store the detection result transmitted by the detection module in a folder; and extract the detection result
  • the name information of the microbial sample corresponding to the detection result in the above, and the name information is set as the file name of the folder;
  • the storage module is further configured to use a preset encryption algorithm to encrypt the detection result in the folder;
  • the preset encryption algorithm includes one or more of asymmetric encryption algorithm, md5 encryption algorithm, and AES encryption algorithm.
  • the intelligent identification module includes an intelligent identification unit
  • the intelligent identification unit is configured to compare the detection result transmitted by the detection module with a preset condition threshold; when one or more items of the detection result exceed the preset condition threshold When the detection result is abnormal, the detection result and detection abnormality information are transmitted to the staff; when any item of the detection result does not exceed the preset condition threshold, the detection is determined The result is no abnormal, and the test result is transmitted to the staff.
  • system further includes an error correction module
  • the error correction module includes an extraction unit, a data processing unit, and a detection result processing unit, wherein:
  • the extraction unit is configured to extract data that exceeds the preset condition threshold in the detection result, and transmit the data that exceeds the preset condition threshold to the data processing unit;
  • the data processing unit is configured to perform errors on the data that exceeds the preset condition threshold in the detection result transmitted by the extraction unit according to the data that does not exceed the preset condition threshold in the detection result Correcting processing, and transmitting the data after the error correction processing to the detection result processing unit;
  • the detection result processing unit is configured to replace the data in the detection result that exceeds the preset condition threshold with the data after the error correction processing, obtain the detection result after the error correction processing, and The detection results after the error correction processing are transmitted to the staff.
  • Figure 1 is a schematic diagram of a microorganism detection method based on third-generation sequencing technology provided by the present invention
  • Figure 2 is a schematic structural diagram of a microorganism detection system based on third-generation sequencing technology provided by the present invention.
  • the embodiment of the present invention provides a microorganism detection method based on the third-generation sequencing technology. As shown in FIG. 1, the method includes:
  • the working principle of the above method is to obtain a microbial sample; use the third-generation sequencing technology to detect the obtained microbial sample to obtain the detection result; perform intelligent identification processing on the obtained detection result to determine whether the detection result is abnormal.
  • the beneficial effects of the above method are: by using the third-generation sequencing technology to detect the obtained microbial samples, the detection results of the microbial samples are obtained; by intelligently identifying the detection results, the abnormal judgment of the detection results is realized.
  • the above method not only realizes the acquisition of the detection result of the microbial sample, but also realizes the abnormal judgment of the detection result by intelligently identifying the detection result; compared with the traditional technology, the above method does not require the cultivation of the microbial sample,
  • the third-generation sequencing technology can be used to obtain the detection results, which greatly shortens the time consumed for detection, and also effectively reduces the cost of microbial detection.
  • the step: using third-generation sequencing technology to detect the microbial sample, and obtaining the detection result includes the following steps:
  • the nanopore is constructed with ⁇ -hemolysin, exonuclease is formed on the outer surface of one side of the nanopore, and cyclodextrin is covalently bound to the inner surface of the nanopore as a sensor;
  • a preset voltage is provided on both sides of the lipid bilayer, so that the exonuclease digests single-stranded DNA, a single base falls into the nanopore, and temporarily interacts with the cyclodextrin in the nanopore.
  • the interaction affects the current flowing through the nanopore, and sequencing is achieved according to the residence time, current, and interference amplitude of each base in the cyclodextrin.
  • the third-generation sequencing technology is a new type of sequencing technology that integrates multiple advantages such as high throughput, rapidity, long read length, and low cost. Its biggest feature is that it does not require PCR amplification and can directly read the target sequence, so the false positive rate is greatly reduced, while avoiding the occurrence of common PCR errors such as base substitution and offset.
  • the third-generation sequencing technology has no advantage over the second-generation sequencing technology, and the error rate is usually around 15%.
  • an accuracy rate of 99.9% can be achieved.
  • the current third-generation sequencing platforms mainly include: Helicos Biosciences' tSMS TM (true single molecular sequencing, parallel single molecule sequencing technology) technology platform, and Pacific Biosciences' SMRT (single molecule real-time, single molecule real-time sequencing by synthesis). Technology) technology platform; FRET-based sequencing technology from Life Technologies of the United States and nanopore single-molecule technology from Ion Torrent of the United States and Oxford Nanopore Technologies of the United Kingdom.
  • nanopore single molecule sequencing technology is simple in structure and low in cost; because it does not need to label nucleotides, and does not require complex optical detection systems (such as laser transmitters and CCD signal acquisition systems). Can directly sequence RNA molecules. At the same time, because it directly detects the characteristic current of each base, it can sequence the modified bases.
  • the beneficial effect of the above method is that the third-generation sequencing technology is used to sequence the nucleic acids in the extracted microbial samples, which improves the sequencing throughput, does not need to go through the library building procedures of the microbial samples, and reduces the occurrence of samples during amplification. The probability of mismatch, and can simplify the preparation process of microbial samples.
  • the microorganism sample includes food, soil, animal body fluid or tissue, and the microorganism includes virus or bacteria.
  • the microbial sample is derived from mammals, such as humans.
  • the microbial sample may be derived from a vertebrate.
  • the microbial samples include: urine, blood, skin, plasma, serum, saliva, wound tissue, wound exudate, biopsy, feces, solid tissue and the like.
  • the samples to be tested are derived from: respiratory tract, genitourinary tract, reproductive tract, central nervous system, etc.
  • the microbial sample can be derived from plants or food.
  • the sample to be tested can also be obtained from soil, air or water in the environment, or a surface in contact with the environment.
  • Microorganisms include viruses or bacteria, such as Salmonella, Campylobacter jejuni, Listeria monocytogenes, Enterobacter sakazakii, cytomegalovirus, human polyoma virus, human herpes virus, Aspergillus flavus, Aspergillus griseus, Aspergillus niger, Mucor racemosa A, Mucor racemosa B, Lactospora, Penicillium expanding, Penicillium Lou, Penicillium digitatum, Rhizopus niger, etc.
  • the source of microbial samples is provided, and the microbial detection method based on the third-generation sequencing technology of the present invention can realize the detection of multiple microorganisms from different sources.
  • the test results are stored in a folder to realize the storage of the test results; and the name information of the microbial sample corresponding to the test result in the test result is set as the file name of the folder, which facilitates the staff to understand the microbial sample
  • the detection result is searched; and the detection result in the folder is encrypted by using a preset encryption algorithm, thereby effectively improving the security of the detection result storage.
  • the preset encryption algorithm includes one or more of asymmetric encryption algorithm, md5 encryption algorithm, and AES encryption algorithm.
  • asymmetric encryption algorithm md5 encryption algorithm
  • AES encryption algorithm multiple encryption algorithms are used to realize the encryption processing of the detection result.
  • the step: performing intelligent recognition processing on the detection result and judging whether the detection result is abnormal including the following steps:
  • the detection result is transmitted to the staff.
  • the acquired detection result is compared with the preset condition threshold to realize the abnormal judgment of the detection result; and when one or more data in the detection result exceeds the preset condition threshold, the judgment is detected
  • the result is abnormal, and the detection result and detection abnormal information are transmitted to the staff to remind the staff that the detection result of the microbial sample obtained by the staff is abnormal; when any data in the detection result does not exceed the preset condition threshold, judge There is no abnormality in the test results, and the test results are transmitted to the staff to realize the staff's acquisition of the test results of the microbial samples.
  • the data that exceeds the preset condition threshold in the detection result is replaced with the data after error correction processing, the detection result after error correction processing is obtained, and the detection result after error correction processing is transmitted to the staff.
  • the data that exceeds the preset condition threshold in the detection result is extracted, and based on the data that does not exceed the preset condition threshold in the detection result, the detection result exceeds the preset condition threshold.
  • the data undergoes error correction processing to obtain the data after the error correction processing, thereby realizing the error correction processing of the data exceeding the preset condition threshold in the detection result; and replacing the data exceeding the preset condition threshold in the detection result with the error Correcting the processed data, thereby achieving the acquisition of the detection results after the error correction processing, and transmitting the detection results after the error correction processing to the staff for display, so as to realize the acquisition of the detection results after the error correction processing by the staff.
  • intelligent recognition processing is performed on the detection result, after judging whether the detection result is abnormal, an abnormal warning can be issued after the abnormality is determined, and the following steps are performed:
  • Step A1 Obtain the environmental information during the detection, and determine the height of the detection stimulus line spectrum corresponding to the environmental information;
  • h is the height of the detection stimulus line spectrum
  • e is the natural constant
  • P is the pressure information in the environmental information
  • c is the concentration obtained from the detection of the microbial sample
  • S is the preset environmental expansion coefficient
  • L is the preset Laser gas intensity
  • ⁇ 0 is the propagation speed of light in the current environmental medium
  • Mw is the molecular mass of the microbial sample
  • T is the temperature in the environmental information
  • ⁇ is the propagation speed of light in vacuum
  • the preset value S is generally set to a value of 0.08
  • the preset value of L is generally set to a value of 0.31 cm.
  • Step A2 Determine the adjustment coefficient corresponding to the environmental information
  • fs is the adjustment coefficient corresponding to the environmental information
  • Step A3 Determine the intelligent identification processing result of the microorganism according to the adjustment coefficient and the height of the detected stimulus line spectrum
  • rt is the result of the intelligent identification processing
  • Sf is the area of the microorganism sample to be tested
  • N is the total amount of the microorganism under the preset standard
  • Step A4 Determine whether the total amount of microorganisms in the detection result is greater than the intelligent identification processing result, if it is greater, whether the detection result is abnormal, perform detection and issue an abnormal warning, otherwise continue to perform subsequent processing.
  • the beneficial effect of the above technical solution is that the above technology can be used to intelligently identify the detection result, determine whether the detection result is abnormal, and provide corresponding early warning processing after the abnormality occurs, and at the same time, use the above technology to intelligently perform the detection result
  • the identification process the influence of environmental information on the detection results of microbial samples is repeatedly considered, so the environment is adjusted by calculating the height of the detection stimulus line spectrum and the adjustment coefficient, so that the calculation results are more consistent with the current environment.
  • the above-mentioned technology Compared with directly comparing the detection result with the threshold value, it is more dynamic, more intelligent, and the detection result is more reliable.
  • a microbial detection system based on the third-generation sequencing technology includes: an acquisition module 21, a detection module 22, and an intelligent identification module 23, wherein:
  • the obtaining module 21 is used to obtain microbial samples
  • the detection module 22 is configured to use the third-generation sequencing technology to detect the microbial sample obtained by the obtaining module 21, obtain the detection result, and transmit the detection result to the intelligent identification module 23;
  • the intelligent identification module 23 is used to perform intelligent identification processing on the detection result transmitted by the detection module 22, and determine whether the detection result is abnormal.
  • the working principle of the above-mentioned system is: the detection module 22 uses the third-generation sequencing technology to detect the microbial samples obtained by the acquisition module 21 to obtain the detection results; the intelligent identification module 23 performs intelligent identification processing on the detection results obtained by the detection module 22, and judges the detection. Whether the result is abnormal.
  • the detection module adopts the third-generation sequencing technology to detect the obtained microbial samples, which realizes the acquisition of the detection results of the microbial samples; and the intelligent recognition processing of the detection results is realized by the intelligent recognition module Judge the abnormality of the detection results; the detection module uses the third-generation sequencing technology to detect the obtained microbial samples, and realizes the acquisition of the detection results of the microbial samples; and intelligently recognizes the detection results through the intelligent recognition module to achieve Abnormal judgment of the detection result; the above system not only realizes the acquisition of the detection result of the microbial sample, but also realizes the abnormal judgment of the detection result by intelligently identifying the detection result; compared with the traditional technology, the above system does not require For the cultivation of microbial samples, the third-generation sequencing technology can be used to obtain the detection results, which greatly reduces the time consumed for detection, and also effectively reduces the cost of microbial detection.
  • system further includes a storage module
  • the detection module is also used to transmit the detection result to the storage module;
  • the storage module is used to store the detection result transmitted by the detection module in a folder; and extract the name information of the microbial sample corresponding to the detection result in the detection result, and store the name information Set to the file name of the folder;
  • the storage module is also used to encrypt the detection results in the folder by using a preset encryption algorithm; in the above technical solution, the storage module stores the detection results transmitted by the detection module in the folder to realize the storage of the detection results; and Set the name information of the microbial sample corresponding to the test result in the test result to the file name of the folder, which facilitates the staff to find the test results of the microbial sample; and the preset encryption algorithm is used to encrypt the test results in the folder , Thereby effectively improving the security of the test results storage.
  • the preset encryption algorithm includes one or more of asymmetric encryption algorithm, md5 encryption algorithm, and AES encryption algorithm.
  • asymmetric encryption algorithm md5 encryption algorithm
  • AES encryption algorithm multiple encryption algorithms are used to realize the encryption processing of the detection result.
  • the intelligent identification module includes an intelligent identification unit
  • the intelligent identification unit is used to compare the detection result transmitted by the detection module with the preset condition threshold; when one or more data in the detection result exceeds the preset condition threshold, judge that the detection result is abnormal, and report to the work
  • the personnel transmits the detection result and detection abnormality information; when any item of the detection result does not exceed the preset condition threshold, it is judged that the detection result is not abnormal, and the detection result is transmitted to the staff.
  • the intelligent recognition unit compares the acquired detection result with the preset condition threshold to realize the abnormal judgment of the detection result; and when one or more data in the detection result exceeds the preset condition threshold , Determine the abnormality of the detection result, and transmit the detection result and detection abnormal information to the staff to remind the staff that the detection result of the microbiological sample obtained by the staff is abnormal; when any of the data in the detection result does not exceed the preset condition threshold At the time, it is judged that there is no abnormality in the detection result, and the detection result is transmitted to the staff, so as to realize the acquisition of the detection result of the microbial sample by the staff.
  • system further includes an error correction module
  • the error correction module includes an extraction unit, a data processing unit and a detection result processing unit, among which,
  • the extraction unit is configured to extract data that exceeds a preset condition threshold in the detection result, and transmit the data that exceeds the preset condition threshold to the data processing unit;
  • the data processing unit is used to perform error correction processing on the data that exceeds the preset condition threshold in the detection result transmitted by the extraction unit according to the data that does not exceed the preset condition threshold in the detection result, and send the error correction processed data to Transmission of detection result processing unit;
  • the detection result processing unit is used to replace the data in the detection result that exceeds the preset condition threshold with the data after the error correction process, obtain the detection result after the error correction process, and transmit the detection result after the error correction process to the staff .
  • the extraction unit extracts data that exceeds the preset condition threshold in the detection result
  • the data processing unit uses the data processing unit to determine the detection result based on the data that does not exceed the preset condition threshold.
  • the data exceeding the preset condition threshold is subjected to error correction processing, and the data after the error correction processing is obtained, so as to realize the error correction processing of the data exceeding the preset condition threshold in the detection result; and the detection result is processed by the detection result processing unit
  • the data exceeding the preset condition threshold is replaced with the data after the error correction processing, thereby realizing the acquisition of the detection results after the error correction processing, and transmitting the detection results after the error correction processing to the staff for display, thus realizing the work
  • the personnel obtains the detection result after the error correction processing.

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Abstract

La présente invention concerne un procédé et un système basés sur une technologie de séquençage de troisième génération pour détecter des micro-organismes, le procédé comprenant les étapes consistant à : acquérir un échantillon microbien; utiliser une technologie de séquençage de troisième génération pour effectuer une détection sur l'échantillon de micro-organisme, et obtenir un résultat de détection ; et effectuer un traitement d'identification intelligent sur le résultat de détection, et déterminer si le résultat de détection est anormal
PCT/CN2021/083090 2020-04-10 2021-03-25 Procédé et système basés sur une technologie de séquençage de troisième génération pour détecter des micro-organismes WO2021203982A1 (fr)

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CN111424075B (zh) * 2020-04-10 2021-01-15 西咸新区予果微码生物科技有限公司 一种基于第三代测序技术的微生物检测方法及系统
CN113789257A (zh) * 2021-07-05 2021-12-14 厦门赛特奥斯生物技术有限公司 一种基于三代测序技术的微生物检测系统
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