A comprehensive approach to identifying bacterial plasmid genomes and their characteristic profiles

Abstract

The present invention provides a comprehensive method for identifying bacterial plasmid genomes and their characteristic maps, wherein the method screens out candidate plasmid sequences and counts basic information; then downloads known plasmid sequence data from a public database, homologously clusters and removes redundancy to construct a reference database; performs characteristic analysis on sequences determined to be plasmids, and comprehensively depicts the characteristic map of bacterial plasmid genomes; evaluates the risk level and corresponding copy number of antibiotic resistance genes carried by plasmids, and comprehensively evaluates the risk level of plasmid resistance genes; counts the plasmid information of each bacterium and performs classification statistics, and describes the complete plasmid information of the bacterial genome provided by the user as a whole. The method of the present invention can be used as a basic tool for hospital-acquired infection, community-acquired infection, and the prevalence and prediction of antibiotic resistance, and will also play a positive role in studying the increased genetic diversity of strains due to horizontal gene transfer within bacteria and the acquisition of new biological traits by recipient bacteria.

Description

Technical Field

[0001] The invention belongs to the field of bioinformatics, and in particular relates to a comprehensive method for identifying bacterial plasmid genomes and their characteristic maps. Background Art

[0002] Bacteria acquire exogenous DNA through horizontal gene transfer. This ability enables them to quickly adapt to the survival pressure brought by environmental changes, provides a strong competitive advantage and may change the relationship with the host. On the one hand, bacterial horizontal gene transfer improves the ability of bacteria to adapt to new environments, and on the other hand, greatly increases the diversity of bacteria. At present, most of the genes known to be involved in horizontal transfer are related to bacterial resistance and pathogenicity. Plasmids are an important carrier of horizontal gene transfer. Plasmid DNA can be transferred not only between bacteria of the same genus, but also between bacteria of different genus through conjugation. It has been confirmed that not only can R plasmids be transferred between different strains of Escherichia coli, but also that Salmonella typhi can transfer R plasmids to Escherichia coli; conversely, Escherichia coli can also transfer R plasmids from different sources to Salmonella typhi and Shigella dysenteriae.

[0003] However, there is still a lack of tools that can accurately and quickly identify bacterial plasmid genomes and their characteristic maps, which also has an impact on the study of the increase in genetic diversity of bacterial species due to horizontal gene transfer and the acquisition of new biological traits by recipient bacteria. Summary of the invention

[0004] Aiming at the technical problem of how to quickly and accurately identify the plasmid genome and its characteristic map in the bacterial genome in the prior art. The present invention provides a comprehensive method for identifying the bacterial plasmid genome and its characteristic map. The method uses high-throughput sequencing technology to obtain strain genome information on a large scale, especially with the help of third-generation sequencing technology, microbial-related public databases and software methods, and orderly integrates and applies to batch bacterial genome analysis to quickly obtain information such as the number of bacterial plasmids, the drug-resistant genes they carry, and the ability of conjugative transfer. Through the integrated analysis of information, it has a good use in studying major public health issues such as hospital-acquired infection outbreaks and antibiotic resistance.

[0005] In one aspect, the present invention provides a comprehensive method for identifying bacterial plasmid genomes and their characteristic profiles, the method comprising:

[0006] (1) Select candidate plasmid sequences from the bacterial genome file provided by the user according to their length and collect basic information, and modify the sequence name to facilitate subsequent statistics;

[0007] (2) Download known plasmid sequence data from public databases, cluster homology and remove redundancy to construct a reference database;

[0008] (3) Characterize the sequences identified as plasmids and comprehensively characterize the characteristic map of bacterial plasmid genomes;

[0009] (4) In combination with the characteristics of the plasmid identification in step (3), the risk level and corresponding copy number of the antibiotic resistance gene carried by the plasmid are evaluated, and the risk level of the plasmid resistance gene is evaluated as a whole;

[0010] (5) Count the plasmid information of each bacterium and classify it, and describe the complete plasmid information of the bacterial genome provided by the user as a whole.

[0011] Furthermore, in step (1) of the present invention, the bacterial genome (genome.fasta) provided by the user is a genome assembled by short sequencing read length or a genome sequence by long sequencing read length; the specific operation of filtering by length is to first count the length of the input genome sequence, and the remaining sequences after removing the longest are all candidate plasmid sequences; the modified sequence name specifically refers to the combination of the genome name provided by the user + Arabic numerals. The specific rule is to sort by sequence length once, such as "genome_1", "genome_2", etc.

[0012] More preferably, the genome effect of the long sequencing read length of the present invention is better.

[0013] Furthermore, in step (2) of the present invention, the reference database is constructed by using the optimal comparison algorithm and parameters to compare the candidate bacterial plasmid sequence with the manually compiled database, filtering it in combination with the specific comparison information to determine whether the sequence is a plasmid sequence, and determining the source and corresponding number of the database corresponding to the plasmid sequence.

[0014] Preferably, in step (2) of the present invention, the public database includes one or more of the NCBI nucleic acid database, the Addgene database, and the PLSDB database.

[0015] Furthermore, the homology clustering and redundancy removal method of the present invention is as follows:

[0016] First, cd-hit software was used to set 95% consistency and coverage for clustering, and then the noise sequences were removed to obtain the sorted plasmid database. The optimal alignment software and parameters used in the present invention are two software parameter combinations of "mash screen-i0.95-v 0.1" + "blastn-evalue 1e-5-perc_identity 90-outfmt 6", and the sequences aligned by both methods were used as candidate plasmids.

[0017] Furthermore, the characteristic analysis in step (3) of the present invention includes analysis of the type and conjugative transfer ability of the plasmid, and integration of two or more drug resistance databases to obtain the number and type of drug resistance genes and virulence factors of the plasmid sequence.

[0018] Furthermore, in step (3) of the present invention, the type of plasmid is mainly determined by plasmidfinder to determine its plasmid lineage and incompatibility, and the parameters are set to default; the evaluation of the ability to transfer by conjugation uses Plascad to divide the candidate plasmids into three major categories: conjugative transfer, non-mobile, and mobile, among which the conjugative transfer is the object of focus; the integration of two or more drug-resistant genome databases specifically refers to two or more of the CARD drug-resistant gene database, Resfinder database, Megares database, NCBI database, and Argannot database, and Abricate is used as an annotation tool, and the annotation of drug-resistant genes ultimately adopts a merging strategy; the identification of virulence factors is mainly annotated with the VFDB database, and the Abricate parameter is the default.

[0019] The drug resistance genes and virulence factor annotations of the present invention are subsequently screened and filtered according to identity>=95% and coverage>=80%.

[0020] In the present invention, in the step (4), the risk level of the drug-resistant gene carried by the plasmid is evaluated, and the ARG_ranker tool is used to classify the drug-resistant gene into two levels according to the drug-resistant gene enrichment information, mobility and host pathogenicity prior knowledge, where level I is the current impact on the host health, and level II is the impact on the host health in the future, and the category and copy number of the drug-resistant gene at each level are output.

[0021] Furthermore, the bacterial plasmid information counted in step (5) of the present invention is classified and counted according to quantity, category, public data source, number and type of drug-resistant genes, antibiotic resistance mechanism, antibiotic information, conjugative transfer ability, and virulence factors.

[0022] In the present invention, in the step (5), the statistical plasmid information refers to summarizing the plasmid information obtained from steps (1) to (4), and the results are presented in a format such as txt / csv / xlsx, and the corresponding results are stored in a corresponding designated folder directory for easy access at any time.

[0023] The method of the present invention further comprises step (6) of analyzing the colinearity between the strain plasmids to visualize the specific location of the structural variation of the strain plasmids.

[0024] Furthermore, in step (6) of the present invention, the colinearity between the strain plasmids is analyzed to visualize the specific location of the structural variation by the following method:

[0025] Select plasmids of the same strain and arrange them in order according to the length of the sequence, or arrange them by strain collection time to display the results. Each strain plasmid is distinguished by a specific color.

[0026] Furthermore, in step (6) of the present invention, the analysis of the colinearity between plasmid genomes is completed using the analysis tool of JCVI; the analysis of the colinearity between plasmid genomes requires the candidate plasmid genome to be annotated with Prokka to obtain the gff file of the protein-coding gene, and then the corresponding cds sequence and the location information of the genome where the gene is located are extracted, processed into the input format required by JCVI, and the colinearity diagram is drawn, and finally a file in PDF format is generated.

[0027] Preferably, the arrangement order of the plasmids of the present invention is arranged by length by default or defined according to one's own needs.

[0028] The method of the present invention also includes step (7) of evaluating the circularization status of all plasmid sequences: using a script tool in combination with strain third-generation sequencing data to evaluate the circularization of all plasmid sequences, and indicating the breakpoint positions of non-circularized plasmids to facilitate subsequent targeted adjustments.

[0029] Furthermore, in step (7) of the present invention, the analysis of plasmid genome circularization is performed using a script tool developed based on Perl, which is only applicable to strains with corresponding third-generation sequencing data. The script tool of the present invention will be able to accurately and quickly identify whether the plasmid genome is circularized and the potential breakpoint positions in order to make subsequent targeted adjustments.

[0030] Preferably, the present invention uses minimap2 to align the third-generation sequencing reads back to the plasmid genome, and divides the aligned reads into complete alignment and partial alignment according to identity>=90% and coverage>=90%. Finally, the svg tool is used to draw the coverage of the regions on both sides of the candidate plasmid sequence loop connection point to clearly and intuitively display the results of whether the plasmid is looped.

[0031] On the other hand, a bacterial plasmid genome feature database can be obtained through the comprehensive method of the present invention for identifying bacterial plasmid genomes and their feature maps.

[0032] By implementing the technical solution of the present invention, the following beneficial effects can be achieved:

[0033] The comprehensive method for identifying bacterial plasmid genomes and their characteristic maps provided by the present invention is applied to the genome analysis of all bacteria. It can quickly obtain information such as the number of bacterial plasmids, the drug-resistant genes they carry, and their conjugative transfer ability. It plays a good role in studying major public health issues such as hospital-acquired infections, community-acquired infections, the prevalence and prediction of antibiotic resistance, and is also very useful for studying the genetic diversity of bacterial species increased by horizontal gene transfer within bacteria and the acquisition of new biological traits by recipient bacteria. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 This is a technical roadmap for a comprehensive method for identifying bacterial plasmid genomes and their characteristic maps in the present invention.

[0035] Figure 2 The bacterial plasmid identification results in Example 1.

[0036] Figure 3 This is the result of colinearity analysis between bacterial plasmid genomes in Example 1.

[0037] Figure 4 This is the result of detecting the circular state of the bacterial plasmid genome in Example 1. DETAILED DESCRIPTION

[0038] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings of the specification. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0039] The experimental methods in the following examples, unless otherwise specified, are all conventional methods, and are performed according to the techniques or conditions described in the literature in the field or according to the product instructions. The materials, reagents, etc. used in the following examples, unless otherwise specified, can all be obtained from commercial channels.

[0040] The present invention provides a comprehensive method for identifying bacterial plasmid genomes and their characteristic maps, the method comprising:

[0041] (1) Select candidate plasmid sequences from the bacterial genome file provided by the user according to their length and count their basic information. Modify the sequence name to facilitate subsequent statistics.

[0042] (2) Download known plasmid sequence data from public databases, cluster homology and remove redundancy to construct a reference database.

[0043] (3) Characterize the sequences identified as plasmids and comprehensively characterize the characteristic map of bacterial plasmid genomes.

[0044] (4) Based on the characteristics of the plasmid identification in step (3), the risk level and corresponding copy number of the antibiotic resistance gene carried by the plasmid are evaluated, and the risk level of the plasmid resistance gene is evaluated as a whole.

[0045] (5) Count the plasmid information of each bacterium and classify it, and describe the complete plasmid information of the bacterial genome provided by the user as a whole.

[0046] Example 1: Identification of plasmids in Acinetobacter baumannii and drawing of their characteristic maps

[0047] In this example, nanopore sequencing was performed on the DNA of ten strains of Acinetobacter baumannii, and the sequencing data of these ten samples were quality controlled, and the adapters were filtered, the reads with a length of less than 500 bp were filtered, and the reads with a quality value Q less than 8 were filtered to generate clean reads; based on the clean reads, each strain was assembled and polished, and the assembly integrity was evaluated, and the genome sequences of these ten baumannii strains were obtained after the evaluation was qualified.

[0048] Based on the assembled genomes of the ten Bauman strains, candidate plasmid sequences were screened, and it was found that the number of candidate plasmids carried by the ten strains ranged from 1 to 4, the length ranged from 8,731 to 692,909 bp, and the GC content distribution ranged from 33.43% to 43.30%. The number of candidate plasmids in the ten strains totaled 24. These sequences were compared with the manually curated plasmid database using two software parameter combinations of mash screen-i0.95-v 0.1" + "blastn-evalue 1e-5-perc_identity 90-outfmt 6". Finally, it was found that 23 sequences could meet the comparison requirements and filtering conditions in the database, so these 23 sequences were determined to be plasmids (the results are shown in the attached figure). Figure 2 There is another sequence for which no corresponding sequence was found in the database.

[0049] The 23 sequences identified as plasmids were analyzed for genomic characteristics. Plasmid lineage identification and incompatibility analysis were performed using plasmidfinder, but no corresponding results were found, which was related to the strain type. Plascad was used to analyze the protein system necessary for autonomous transfer in the plasmid sequence to identify its transferability. Among them, 10 plasmid sequences were classified as conjugative transfer, 4 plasmids were mobile plasmids but lacked autonomous transfer ability, and the remaining 9 plasmid sequences were non-transferable plasmid sequences; Abricate was used as an annotation tool to annotate the 23 plasmid sequences using the Resfinder database, Megares database, NCBI database, Argannot database, CARD resistance gene database, and VFDB database, and the Abricate parameters were default. The above-mentioned resistance gene and virulence factor annotations were subsequently screened and filtered according to identity>=95% and coverage>=80%. The final statistical results of all the characteristics of the 23 plasmids are as follows:

[0050] #Plasmids And AMR genes Conjugative Number Mobilizable Number None-Mobilizable Number Total Plasmids 10(43.48％) 4(17.39％) 9(39.13％) 23(100％) AMR genes-bearing plasmids 10(71.43％) 0(0％) 4(28.57％) 14(100％) AMR genes 10(37.04％) 0(0％) 17(62.96％) 27(100％)

[0051] From the above data, it can be seen that these ten conjugative transfer plasmids all carry the blaOXA-23 resistance gene, which is mainly resistant to β-lactamase antibiotics. The four plasmids that cannot move autonomously do not carry resistance genes. In addition, the non-mobile plasmids carry more types of resistance genes, which may be related to the strain type.

[0052] Embodiment 2:

[0053] This example uses the JCVI analysis tool to complete the colinearity analysis between plasmid genomes. It is necessary to annotate the candidate plasmid genome with prokka to obtain the gff file of the protein-coding gene, then extract the corresponding cds sequence and the location information of the genome where the gene is located, process it into the input format required by JCVI, draw the colinearity diagram, and finally generate a pdf format file. This example focuses on the colinearity between 10 conjugative transfer plasmids. By default, they are arranged according to the length of the sequence. For the sake of display beauty, equal length processing is performed (as shown in the attached figure). Figure 3 As shown in Figure 2 ). From the colinearity results of the 10 conjugative transfers, except for the inversion of large fragments, the overall colinearity is good, which may indicate that this batch of conjugative transfer plasmids originated from the same ancestor and spread in a short period of time.

[0054] Embodiment 3:

[0055] This embodiment uses a script tool developed based on perl for analysis, and the script tool of this embodiment is only applicable to strains with corresponding third-generation sequencing data. The script tool of this embodiment will be able to accurately and quickly identify whether the plasmid genome is circular and the potential breakpoint position in order to make subsequent targeted adjustments. The specific steps of the script tool are to use minimap2 to align the third-generation sequencing reads back to the plasmid genome, and divide the aligned reads into complete alignment and partial alignment according to identity>=90% and coverage>=90%. Finally, the svg tool is used to draw the coverage of the areas on both sides of the candidate plasmid sequence circular connection point, clearly and intuitively showing the results of whether the plasmid is circular. Specifically, this embodiment uses the third-generation error-corrected data to judge the circular status of these 10 plasmids that can be conjugated and transferred, and uses one of the plasmid results for display (as shown in the attached figure). Figure 4 shown).

[0056] The above results are because: the middle rectangular bar represents the sequence to be detected (the gray line perpendicular to the rectangle represents the connection point of the genome loop); the upper part of the rectangular bar is the reads that are completely aligned to the genome, and the lower part of the rectangular bar is the reads that are partially aligned to the genome (gray represents reads on the forward alignment, black represents reads on the reverse alignment, and light gray represents reads fragments that are not aligned to the genome). It can be seen that above the rectangular bar, there is an even coverage of fully aligned reads, both forward and reverse, and can completely cross the areas on both sides of the gray vertical line. Therefore, the software determines that the contig sequence is looped.

[0057] The present invention has been described in detail above. It will be apparent to those skilled in the art that the present invention may be implemented in a wide range under equivalent parameters, concentrations and conditions without departing from the spirit and scope of the present invention and without the need for unnecessary experimentation. Although the present invention provides specific embodiments, it should be understood that further improvements may be made to the present invention. In short, according to the principles of the present invention, this application intends to include any changes, uses or improvements to the present invention, including changes made by conventional techniques known in the art that depart from the scope disclosed in this application. Applications of some of the basic features may be made within the scope of the following appended claims.

Claims

1. A comprehensive method for identifying bacterial plasmid genomes and their characteristic profiles, characterized in that: The method comprises: (1) Select candidate plasmid sequences from the bacterial genome file provided by the user according to their length and collect basic information, and modify the sequence name to facilitate subsequent statistics; (2) Download known plasmid sequence data from public databases, cluster homology and remove redundancy to construct a reference database; (3) Characterize the sequences identified as plasmids and comprehensively characterize the characteristic map of bacterial plasmid genomes; (4) In combination with the characteristics of the plasmid identification in step (3), the risk level and corresponding copy number of the antibiotic resistance gene carried by the plasmid are evaluated, and the risk level of the plasmid resistance gene is evaluated as a whole; (5) Count the plasmid information of each bacterium and classify it, and describe the complete plasmid information of the bacterial genome provided by the user as a whole; (6) Analyze the colinearity between strain plasmids to visualize the specific location of strain plasmid structural variation; select plasmids of the same strain and arrange them in order according to sequence length information or support arrangement by strain collection time to display the results. Each strain plasmid is distinguished by a specific color; Step (2) constructing the reference database is to use the optimal comparison algorithm and parameters to compare the candidate bacterial plasmid sequence with the manually sorted database, filter it in combination with the specific comparison information, determine whether the sequence is a plasmid sequence, and determine the source and corresponding number of the database corresponding to the plasmid sequence; The characteristic analysis in step (3) includes analysis of the type and conjugative transfer ability of the plasmid, and integration of two or more drug resistance databases to obtain the number and type of drug resistance genes and virulence factors of the plasmid sequence.

2. A comprehensive method for identifying bacterial plasmid genomes and their characteristic profiles according to claim 1, characterized in that: The bacterial plasmid information counted in step (5) is classified and counted according to quantity, category, public data source, number and type of drug-resistant genes, antibiotic resistance mechanism, antibiotic information, conjugative transfer ability, and virulence factors.

3. A comprehensive method for identifying bacterial plasmid genomes and their characteristic profiles according to claim 1, characterized in that: The method also includes step (7) of evaluating the circularization status of all plasmid sequences: using a script tool in combination with strain third-generation sequencing data to evaluate the circularization status of all plasmid sequences, and indicating the breakpoint positions of non-circularized plasmids to facilitate subsequent targeted adjustments.

4. A bacterial plasmid genome characteristic database system obtained by using the comprehensive method for identifying bacterial plasmid genomes and their characteristic maps as described in any one of claims 1 to 3.

5. Application of the comprehensive method for identifying bacterial plasmid genomes and their characteristic maps as described in any one of claims 1 to 3 in studying the increased genetic diversity of bacterial species due to horizontal gene transfer within bacteria and the acquisition of new biological traits by recipient bacteria.

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