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WO2023006175A1 - Procédé de classification d'au moins une séquence d'acide nucléique et appareil, programme informatique, support de stockage lisible par ordinateur et image numérique - Google Patents

Procédé de classification d'au moins une séquence d'acide nucléique et appareil, programme informatique, support de stockage lisible par ordinateur et image numérique Download PDF

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Publication number
WO2023006175A1
WO2023006175A1 PCT/EP2021/070834 EP2021070834W WO2023006175A1 WO 2023006175 A1 WO2023006175 A1 WO 2023006175A1 EP 2021070834 W EP2021070834 W EP 2021070834W WO 2023006175 A1 WO2023006175 A1 WO 2023006175A1
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WO
WIPO (PCT)
Prior art keywords
nucleic acid
acid sequence
information measure
information
digital image
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Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
PCT/EP2021/070834
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German (de)
English (en)
Inventor
Andreas Emanuel Posch
Markus Dehler
Manuel Ebert
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Siemens AG
Siemens Corp
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Siemens AG
Siemens Corp
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
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Priority to PCT/EP2021/070834 priority Critical patent/WO2023006175A1/fr
Publication of WO2023006175A1 publication Critical patent/WO2023006175A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B30/00—ICT specially adapted for sequence analysis involving nucleotides or amino acids

Definitions

  • the present invention relates to methods for classifying at least one nucleic acid sequence, at least one selective enrichment of at least one nucleic acid target population, a device that is designed to carry out such a method, a corresponding computer program that enables such a method to be carried out, a computer-readable storage medium for this and a digital image that is also designed to carry out the method described.
  • Infections caused by pathogens such as bacteria, viruses, fungi and/or parasites pose a major threat to humans and are responsible for a large number of illnesses and/or deaths worldwide.
  • Strategies to combat infection include appropriate prevention, such as vaccination, or appropriate treatment, such as antibiotics or antivirals.
  • Detection of an acute infection, such as a pathogen infection, in a subject, such as a human can be accomplished in a variety of ways, one of which is detection of pathogen nucleic acid sequences in a sample from the subject, or in other examples, detection of pathogens.
  • a determination of nucleic acid sequences in the sample can be carried out. This determination can be carried out, for example, using detection technologies based on sequencing. However, it can also be carried out using detection technologies based on hybridization.
  • Examples of this include, but are not limited to, polymerase chain reactions, micro-array detection methods, dideoxy methods according to ski or next-generation sequencing methods.
  • the complex samples from the subject itself include complex biological sample materials such as blood, urine, or other biospecimens.
  • a selective enrichment of DNA, such as pathogen DNA, represents an approach to improve the signal-to-noise ratio for the detection of nucleic acid sequences from human samples.
  • EP3529375.A1 describes a selective enrichment of nucleic acid sequences from microorganisms that uses differences in certain genomic signatures, more precisely specific primers, in order to selectively amplify nucleic acid sequences of the microorganisms, for example pathogen DNA.
  • These specific primers can be used to preferentially amplify particular target sequences by selecting them to reveal differences in frequency and/or context between that target and background.
  • These target sequences can include, for example, the genomes of human pathogenic organisms, in particular bacteria.
  • the target of selective amplification corresponds to a large collection of microbial genomes and the subject representing the background nucleic acid sequences corresponds to the human genome.
  • nucleic acid libraries which are obtained, for example, by selective but comprehensive amplification
  • the object of the invention is to specify a method which makes it possible to determine and appropriately classify such amplification products and/or amplification or contamination artifacts.
  • a method for classifying at least one nucleic acid sequence of at least one selective enrichment of at least one nucleic acid target population is provided, wherein the nucleic acid target population comprises at least one nucleic acid sequence segment and wherein the at least one nucleic acid sequence is classified by means of at least one information measure derived from a detection of at least one nucleic acid sequence segment.
  • the procedure includes the following steps:
  • Selective enrichment is to be understood, for example, as not exclusively selective amplification.
  • Selective amplification is amplification from a predefined nucleic acid target population using a nucleic acid amplification method, for example using enzymatic amplification.
  • Selective enrichment can also include enzyme-based enrichment. This can be done, for example, but not exclusively by polymerase, by specific primers, for example by k-mers. This allows certain target sequences to be preferentially amplified by being selected in such a way that differences in frequency and/or context between this target and the background are shown.
  • a nucleic acid sequence is a defined sequence of DNA or RNA bases.
  • a nucleic acid sequence is also to be understood as meaning an enrichment product or amplification product of the selective enrichment or of the selective amplification.
  • a nucleic acid target population is a particular collection of nucleic acid sequences.
  • a nucleic acid sequence section can be an entire genome or just a part of the genome.
  • the smallest unit of a nucleic acid sequence segment is two base pairs of a nucleic acid sequence, the largest unit is all of the nucleic acid sequences present in an organism or in a pathogen.
  • a classification of a nucleic acid sequence is to be understood as an assignment of the nucleic acid sequence to a specific group of enrichment products or amplification products, whether they are of an informative nature, i.e. of such a nature that they can be assigned to actual positive pathogens, or whether they are not of an informative nature , i.e. such that they have to be assigned to false positive pathogens.
  • Non-informative enrichment products or amplification products can also be enrichment artifacts or amplification artifacts, for example due to non-specific amplification lification reactions or artificial amplification products include. They can also include contamination artefacts, for example due to subsequent contamination of the sample, for example during sample removal or sample preparation.
  • a detection of at least one nucleic acid sequence segment can, for example, but not exclusively, take place through a plurality of sequencing reads or next-generation sequencing reads.
  • Sequencing reads are a sequence of base pairs or base pair probabilities of a nucleic acid sequence segment determined using Sanger sequencing technology.
  • the length of such reads is usually several hundred base pairs.
  • Next-generation sequencing reads are a sequence of base pairs or base pair probabilities of a nucleic acid sequence segment determined using next-generation sequencing technology.
  • the length of such reads is usually 75 to several hundred base pairs, but can also include thousands of base pairs.
  • a measure of information according to the invention comprises information on the nucleic acid sequence sections which is obtained from experiments and/or experiment databases. By appropriately deriving an information measure, nucleic acid sequences can be assigned to specific groups of enrichment products or amplification products.
  • An information measure according to the invention can also include a number of reads of the at least one nucleic acid sequence segment and/or a number of bases per read of the at least one nucleic acid sequence segment.
  • Sectioning can also include a selection of a suitable information measure from a previous experiment or series of experiments and is not limited to a single execution of the method.
  • the at least one information measure can also be determined, at least in part, by means of a computer-aided method.
  • a computer-aided method is to be understood, for example, but not exclusively, as a method that includes program parts that support and/or optimize the physical method using artificial intelligence.
  • the quality of the information derived from the underlying selective enrichment can be increased by this non-automated method.
  • a classification of at least one nucleic acid sequence based on the derived at least one information measure is also to be understood as a recognition, in particular a specific recognition of the at least one nucleic acid sequence.
  • the invention thus uses a generated possibility of assignment in order to provide a sensitive and specific determination of nucleic acid sequences and thus also to increase the quality of the underlying selective enrichment, for example in order to separate treatment-relevant results from non-treatment-relevant results.
  • the at least one information measure includes a determination of at least one limit value.
  • a limit value are the coverage of nucleic acid sequences of the nucleic acid target population or the number of reads achieved or sequencing depth for nucleic acid sequences of the nucleic acid target population.
  • the limit value itself can also be a limit value function, such as relating to a uniformity ratio cover nucleic acid sequences of the nucleic acid target population.
  • limit values or limit value functions can be used, for example, but not exclusively, to determine certain hotspots in a genome that result from certain enrichment artifacts or amplification artifacts.
  • the at least one information measure includes a coverage of the at least one nucleic acid sequence section. Coverage is a percentage of base pairs of a certain nucleic acid sequence that can be covered by reads. The higher the coverage, the higher the probability that the nucleic acid sequence is actually present in the sample. Thus, coverage is an important measure to determine the presence of a nucleic acid sequence.
  • At least one information measure comprises a detection level of the at least one nucleic acid sequence section.
  • a detection level is to be understood, for example, but not exclusively, as a sequencing depth of the at least one nucleic acid sequence section.
  • a sequencing depth is a number of reads that can be allocated to a certain nucleic acid sequence. The higher the sequencing depth, the higher the concentration of the nucleic acid sequence in the sample. The sequence depth is thus an important measure for determining the presence of a nucleic acid sequence. For example, a minimum sequencing depth can be used to differentiate between signal and noise.
  • the sequencing depth can be determined by means of an absolute or relative frequency determination and can also include a detection level or an abundance level.
  • the at least one information measure and one further information measure form a multivariate information measure.
  • the multivariate information measure includes an evenness ratio.
  • the uniformity ratio is calculated on the one hand based on a number of unique base pairs found per assigned read and on the other hand on an estimated number of unique base pairs found per assigned read, assuming a homogeneous distribution of the reads over a nucleic acid sequence with a paired read length as a suitable upper bound.
  • the nucleic acid sequence comprises at least one sequence with a specific function or at least one sequence which can be assigned specifically to a functional class or a pathogen or a pathogen class.
  • a sequence with a specific function can be understood, for example, but not exclusively, as a sequence of individual genes, for example antibiotic resistance genes or virulence genes, but also a sequence of an entire genome of a pathogen.
  • classification of the at least one nucleic acid sequence differentiates it from other nucleic acid sequences.
  • These further nucleic acid sequences can also include living, virulent, proliferating, intact and/or non-intact cells. A more sensitive and/or more specific determination of the nucleic acid sequences can also be achieved in this way and thus also an increase in the quality of the information derived from the underlying selective enrichment.
  • the other nucleic acid sequences include other products of the at least one selective enrichment.
  • Other products can, for example, but not exclusively, be non-specific amplification artifacts in order to enable a more specific determination of the nucleic acid sequences.
  • a device for classifying at least one nucleic acid sequence includes all means to classify the at least one nucleic acid sequence and can also be designed to carry out additional method steps, such as the selective enrichment itself.
  • the present invention describes a computer program that can be loaded into a memory of a programmable controller or a computing unit of a server unit and/or a device according to the invention. All or various previously described embodiments of the method according to the invention can be executed with this computer program if the computer program runs in the controller or control device of the server unit and/or the device according to the invention.
  • the computer program may require program means, for example libraries and auxiliary functions, in order to implement the corresponding embodiments of the method.
  • a software would be placed under protection with which one of the above-described embodiments of the method according to the invention can be carried out or which carries out this embodiment.
  • the software can be a source code that still has to be compiled and linked or that only needs to be interpreted, or it can be an executable software code that only needs to be loaded into the corresponding processing unit for execution.
  • the present invention also relates to a computer-readable storage medium, e.g. a DVD, a Blu-ray disc, a hard drive or a USB stick, on which electronically readable control information, in particular software, is stored. If this control information is read from the storage medium and stored in a controller or computing unit of a server unit and/or a device according to the invention, all embodiments according to the invention of the method described above can be carried out.
  • a computer-readable storage medium e.g. a DVD, a Blu-ray disc, a hard drive or a USB stick
  • the invention also relates to a digital image designed to classify at least one nucleic acid sequence.
  • the digital image includes a digital representation of the device according to the invention.
  • the digital representation includes a digital description of one or more physical objects.
  • the digital representation can also include a behavioral model of one or more physical objects.
  • the digital image comprises an interface between the digital representation of the device and the device for two-way communication.
  • the interface allows, for example, recording of data from the device at different points in time and can also include acquisition of a behavioral model of the device in real time. It can be used to collect statistical metrics and/or for analysis and/or optimization.
  • the digital image itself is thus designed to carry out the method according to the invention described in a restricted manner.
  • the digital image additionally includes the device. This enables the method according to the invention to be carried out in an optimized manner, since the device can be connected more easily to the interface of the digital image.
  • FIG. 2 shows method results in tabular form and exemplary information measures used for the method according to the invention.
  • 1 shows a flow chart of a method according to the invention. The method comprises the method steps 101 to 105, whereby in the description of the method steps 101 to 105, parts of the description including the corresponding ones in connection with the reference symbols introduced in FIG. 2 can also be used.
  • Method steps 101 to 105 can be carried out manually, semi-automatically or automatically and/or by means of a described device according to the invention which is designed to carry out such a method and/or by a corresponding computer program which executes such a method made possible and/or by a computer-readable storage medium for this purpose and/or by a digital image, which is also designed to carry out the method described.
  • a first method step 101 characterizes the start of a classification of at least one nucleic acid sequence 202 at least one selective enrichment of at least one nucleic acid target population, wherein the nucleic acid target population comprises at least one nucleic acid sequence section.
  • Selective enrichment is to be understood, for example, as not exclusively selective amplification.
  • Selective amplification is amplification from a predefined nucleic acid target population using a nucleic acid amplification method, for example using enzymatic amplification.
  • a nucleic acid sequence 202 is a defined sequence of DNA or RNA bases.
  • a nucleic acid sequence 202 is also to be understood as meaning an enrichment product or amplification product of the selective enrichment or of the selective amplification.
  • a nucleic acid sequence segment can be an entire genome or just a part of the genome.
  • the smallest unit A nucleic acid sequence section is two base pairs of a nucleic acid sequence, the largest unit is the largest unit is all of the nucleic acid sequences present in an organism or in a pathogen.
  • a detection of at least one nucleic acid sequence section can, for example, but not exclusively, take place by means of several sequencing reads or next-generation sequencing reads. Sequencing reads are a sequence of base pairs or base pair probabilities of a nucleic acid sequence segment determined using Sanger sequencing technology. The length of such reads is usually several hundred base pairs.
  • Next-generation sequencing reads are a sequence of base pairs or base pair probabilities of a nucleic acid sequence segment determined using next-generation sequencing technology.
  • the length of such reads is usually 75 to several hundred base pairs, but can also include thousands of base pairs.
  • Method step 103 characterizes the derivation of at least one information measure 205, 206 based on the detected at least one nucleic acid sequence section.
  • a measure of information 205, 206 according to the invention includes information on the nucleic acid sequence segments which is obtained from experiments and/or experiment databases 201. By appropriately deriving an information measure 205, 206, nucleic acid sequences 202 can be assigned to specific groups of enrichment products or amplification products.
  • An information measure 205, 206 according to the invention can also include a number of reads of the at least one nucleic acid sequence segment and/or a number of bases per read of the at least one nucleic acid sequence segment.
  • the derivation of the at least one information measure 205, 206 based on the detected at least one nucleic acid sequence section can also be a selection of a suitable information measure 205, 206 from a previous experiment or a series of experiments include and is not limited to a singular execution of the process.
  • At least one nucleic acid sequence 202 is classified based on the derived at least one information measure 205, 206.
  • Classification of at least one nucleic acid sequence 202 based on the derived at least one information measure 205, 206 also includes recognition, in particular specific recognition of the at least one Nucleic acid sequence 202 to understand.
  • a last method step 105 characterizes an end of a classification of at least one nucleic acid sequence 202 at least one selective enrichment of at least one nucleic acid target population, wherein the nucleic acid target population comprises at least one nucleic acid sequence section.
  • FIG. 2 shows method results in tabular form as well as information dimensions 205, 206, 207 used for the method according to the invention.
  • a first information measure 205 and a second information measure 206 are involved, which together form an exemplary multivariate information measure 207 .
  • the first information measure 205 is an average number of unique base pairs observed per read for a nucleic acid sequence, which in the experiment shown is a quotient between a product of a percentage coverage of a nucleic acid sequence at a detection level of one and a length of one nucleus acid sequence and a number of reads associated with a nucleic acid sequence.
  • the second information measure 206 is an estimated number of unique base pairs per read when the reads are evenly distributed over the nucleic acid sequence that in the experiment shown comprises a quotient between a length of a nucleic acid sequence and a number of reads assigned to a nucleic acid sequence.
  • the multivariate information measure 207 formed from these two information measures 205, 206, in the experiment shown a uniformity ratio, comprises a quotient of the first information measure 205 and the second information measure 206 for a case that an estimated number of base pairs per read is less than 300 and comprises a quotient of the first information measure 205 and 300 for a case that a number of estimated base pairs per read is greater than or equal to 300.
  • the limit of 300 shown in this example corresponds to a so-called paired-end next-generation sequencing read length of 150 per read and must be selected according to the next-generation sequencing read length.
  • the method results in tabular form show for all test samples 201 that a specific nucleic acid sequence 202, in the present example a pathogen that is actually present, can in all cases be classified with a significantly higher quality than a first further nucleic acid sequence 203, in the present example a first false-positive organism or also as a second further nucleic acid sequence 204, in the present example a second false-positive organism.
  • the percentages shown in FIG. 2 correspond directly to a multivariate information measure 207, in this example a uniformity ratio.
  • the classification 104 of at least one nucleic acid sequence 202 of at least one selective enrichment of at least one nucleic acid target population by means of an information measure 205, 206, here by means of a multivariate information measure 207 is not limited to this multivariate information measure 207 .
  • Such a classification 104 can also be carried out using a single univariate information measure 205, 206 or using several univariate and/or multivariate information measures 205, 206, 207.
  • the at least one information measure 205, 206 can also be determined, at least in part, using a computer-aided method.
  • a computer-aided method is to be understood, for example, but not exclusively, as a method that includes program parts that support and/or optimize the physical method using artificial intelligence.
  • An information measure 205, 206, 207 can include a determination of at least one limit value. Examples of such a limit value are the coverage of nucleic acid sequences 202 of the nucleic acid target population or the number of reads achieved or also the sequencing depth for nucleic acid sequences 202 of the nucleic acid target population.
  • An information measure 205, 206, 207 can likewise also include a detection level of the at least one nucleic acid sequence section, such as a sequencing depth of the at least one nucleic acid sequence section.
  • a sequencing depth is a number of reads that a certain nucleic acid sequence 202 can be assigned. The higher the sequencing depth, the higher the concentration of the nucleic acid sequence 202 in the sample. The sequencing depth is thus an important measure for determining the presence of a nucleic acid sequence 202 . For example, a minimum sequencing depth can be used to differentiate between signal and noise.
  • the classification 104 of the at least one nucleic acid sequence 202 includes a delimitation to further nucleic acid sequences 203, 204.
  • These further nucleic acid sequences 203, 204 can also comprise living, virulent, proliferating, intact and/or non-intact cells.
  • a more sensitive and/or more specific determination of the nucleic acid sequences 202 can be achieved and thus also an increase in the quality of the information derived from the underlying selective enrichment.
  • the further nucleic acid sequences 203 204 can also include further products of the at least one selective enrichment.
  • Other products can, for example, but not exclusively, be non-specific amplification artefacts in order to enable the nucleic acid sequences 202 to be determined more specifically.
  • the invention relates to a method for classifying at least one nucleic acid sequence, at least one selective enrichment of at least one nucleic acid target population, a device that is designed to carry out such a method, a corresponding computer program that enables such a method to be carried out, a computer-readable storage medium for this and a digital image that is also designed to carry out the method described.
  • the nucleic acid target population comprises at least one nucleic acid sequence segment and the at least one nucleic acid sequence is classified using at least one information measure derived from a detection of at least one nucleic acid sequence segment.

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  • Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)

Abstract

L'invention concerne un procédé de classification d'au moins une séquence d'acide nucléique d'au moins une amélioration sélective d'au moins une population cible d'acides nucléiques, un appareil qui est conçu pour mettre en œuvre un tel procédé, un programme informatique correspondant qui permet de mettre en œuvre un tel procédé, un support de stockage lisible par ordinateur associé et une image numérique qui est également conçue pour mettre en œuvre le procédé décrit. La population cible d'acides nucléiques comprend au moins un segment de séquence d'acide nucléique et la classification de ladite séquence d'acide nucléique a lieu au moyen d'au moins une mesure d'informations obtenue par détection d'au moins un segment de séquence d'acide nucléique.
PCT/EP2021/070834 2021-07-26 2021-07-26 Procédé de classification d'au moins une séquence d'acide nucléique et appareil, programme informatique, support de stockage lisible par ordinateur et image numérique Ceased WO2023006175A1 (fr)

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PCT/EP2021/070834 WO2023006175A1 (fr) 2021-07-26 2021-07-26 Procédé de classification d'au moins une séquence d'acide nucléique et appareil, programme informatique, support de stockage lisible par ordinateur et image numérique

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PCT/EP2021/070834 WO2023006175A1 (fr) 2021-07-26 2021-07-26 Procédé de classification d'au moins une séquence d'acide nucléique et appareil, programme informatique, support de stockage lisible par ordinateur et image numérique

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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP3529375A1 (fr) 2016-12-21 2019-08-28 Siemens Healthcare GmbH Appauvrissement en matériel génétique intégré par amplification d'organismes non cibles à l'aide de k-mères à abondance différentielle
WO2020106987A1 (fr) * 2018-11-21 2020-05-28 Karius, Inc. Détection et prédiction de maladie infectieuse
WO2020178575A1 (fr) * 2019-03-04 2020-09-10 St George's Hospital Medical School Détection et profilage de résistance aux antibiotiques de micro-organismes

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP3529375A1 (fr) 2016-12-21 2019-08-28 Siemens Healthcare GmbH Appauvrissement en matériel génétique intégré par amplification d'organismes non cibles à l'aide de k-mères à abondance différentielle
US20190345569A1 (en) * 2016-12-21 2019-11-14 Siemens Healthcare Gmbh Amplification-integrated genetic material depletion of non-target organisms using differentially abundant k-mers
WO2020106987A1 (fr) * 2018-11-21 2020-05-28 Karius, Inc. Détection et prédiction de maladie infectieuse
WO2020178575A1 (fr) * 2019-03-04 2020-09-10 St George's Hospital Medical School Détection et profilage de résistance aux antibiotiques de micro-organismes

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
WANG MING ET AL: "Nanopore Targeted Sequencing for the Accurate and Comprehensive Detection of SARS-CoV-2 and Other Respiratory Viruses", SMALL, vol. 16, no. 32, 24 August 2020 (2020-08-24), pages 2002169, XP055911720, ISSN: 1613-6810, Retrieved from the Internet <URL:https://onlinelibrary.wiley.com/doi/full-xml/10.1002/smll.202002169> DOI: 10.1002/smll.202002169 *

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