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The geno-spatio analysis of Mycobacterium tuberculosis complex in hot and cold spots of Guangxi, China
Virasakdi Virasakdi
Epidemiology Unit,Faculty of Medicine, Prince of Songkla University
Corresponding Author
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This work is licensed under a CC BY 4.0 License. Read Full License
View the published version at BMC Infectious Diseases.
Background At present, there are few studies on polymorphism of Mycobacterium tuberculosis (Mtb) gene and how it affects the TB epidemic. This study aimed to document the differences of polymorphisms between tuberculosis hot and cold spot areas of Guangxi Zhuang Autonomous Region, China.
Methods The cold and hot spot areas, each with 3 counties, had been pre-identified by TB incidence for 5 years from the surveillance database.
Whole genome sequencing analysis was performed on all sputum Mtb isolates from the detected cases during January and June 2018. Single nucleotide polymorphism (SNP) of each isolate compared to the H37Rv strain were called and used for lineage and sub-lineage identification. Pairwise SNP differences between every pair of isolates were computed. Analyses of Molecular Variance (AMOVA) across counties of the same hot or cold spot area and between the two areas were performed.
Results As a whole, 59.8% (57.7% sub-lineage 2.2 and 2.1% sub-lineage 2.1) and 39.8% (17.8% sub-lineage 4.4, 6.5% sub-lineage 4.2 and 15.5% sub-lineage 4.5) of the Mtb strains were Lineage 2 and Lineage 4 respectively. The percentages of sub-lineage 2.2 (Beijing family strains) are significantly higher in hot spots. Through the MDS dimension reduction, the genomic population structure in the three hot spot counties is significantly different from those three cold spot counties (T-test p = 0.05). The median of SNPs distances among Mtb isolates in cold spots was greater than that in hot spots (897 vs 746, Rank-sum test p < 0.001). Three genomic clusters, each with genomic distance ≤ 12 SNPs, were identified with 2, 3 and 4 consanguineous strains. Two clusters were from hot spots and one was from cold spots.
Conclusion Narrower genotype diversity in the hot area may indicate higher transmissibility of the Mtb strains in the area compared to those in the cold spot area.
Keywords
Tuberculosis; genotypes; polymorphisms; spatial; influence
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CURRENT STATUS: Published
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Posted 01 Jun, 2020
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On 01 Jul, 2020
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Editorial decision: Accept
On 20 Jun, 2020
Editor assigned
On 24 May, 2020
Submission checks complete
On 23 May, 2020
Editor invited
On 23 May, 2020
No comments provided
Editorial decision: Minor revision
On 22 May, 2020
Reviewer #2 agreed
On 01 May, 2020
Review #1 received
Received 01 May, 2020
Review #2 received
Received 01 May, 2020
Reviewers invited
Invitations sent on 01 May, 2020
Reviewer #1 agreed
On 01 May, 2020
Editor assigned
On 13 Apr, 2020
Submission checks complete
On 12 Apr, 2020
Editor invited
On 12 Apr, 2020
No comments provided
Editorial decision: Major revision
On 04 Apr, 2020
Review #2 received
Received 23 Mar, 2020
Review #1 received
Received 22 Mar, 2020
Reviewer #2 agreed
On 09 Mar, 2020
Reviewer #1 agreed
On 08 Mar, 2020
Reviewers invited
Invitations sent on 06 Mar, 2020
Editor assigned
On 01 Mar, 2020
Submission checks complete
On 29 Feb, 2020
Editor invited
On 29 Feb, 2020
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Infectious Diseases
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This preprint is under consideration at BMC Infectious Diseases. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research article
The geno-spatio analysis of Mycobacterium tuberculosis complex in hot and cold spots of Guangxi, China
Virasakdi Virasakdi
Epidemiology Unit,Faculty of Medicine, Prince of Songkla University
Corresponding Author
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
Version 3
Posted 01 Jun, 2020
Published
On 01 Jul, 2020
No community comments so far
Editorial decision: Accept
On 20 Jun, 2020
Editor assigned
On 24 May, 2020
Submission checks complete
On 23 May, 2020
Editor invited
On 23 May, 2020
No comments provided
Editorial decision: Minor revision
On 22 May, 2020
Reviewer #2 agreed
On 01 May, 2020
Review #1 received
Received 01 May, 2020
Review #2 received
Received 01 May, 2020
Reviewers invited
Invitations sent on 01 May, 2020
Reviewer #1 agreed
On 01 May, 2020
Editor assigned
On 13 Apr, 2020
Submission checks complete
On 12 Apr, 2020
Editor invited
On 12 Apr, 2020
No comments provided
Editorial decision: Major revision
On 04 Apr, 2020
Review #2 received
Received 23 Mar, 2020
Review #1 received
Received 22 Mar, 2020
Reviewer #2 agreed
On 09 Mar, 2020
Reviewer #1 agreed
On 08 Mar, 2020
Reviewers invited
Invitations sent on 06 Mar, 2020
Editor assigned
On 01 Mar, 2020
Submission checks complete
On 29 Feb, 2020
Editor invited
On 29 Feb, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Infectious Diseases
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published version at BMC Infectious Diseases.
Background At present, there are few studies on polymorphism of Mycobacterium tuberculosis (Mtb) gene and how it affects the TB epidemic. This study aimed to document the differences of polymorphisms between tuberculosis hot and cold spot areas of Guangxi Zhuang Autonomous Region, China.
Methods The cold and hot spot areas, each with 3 counties, had been pre-identified by TB incidence for 5 years from the surveillance database.
Whole genome sequencing analysis was performed on all sputum Mtb isolates from the detected cases during January and June 2018. Single nucleotide polymorphism (SNP) of each isolate compared to the H37Rv strain were called and used for lineage and sub-lineage identification. Pairwise SNP differences between every pair of isolates were computed. Analyses of Molecular Variance (AMOVA) across counties of the same hot or cold spot area and between the two areas were performed.
Results As a whole, 59.8% (57.7% sub-lineage 2.2 and 2.1% sub-lineage 2.1) and 39.8% (17.8% sub-lineage 4.4, 6.5% sub-lineage 4.2 and 15.5% sub-lineage 4.5) of the Mtb strains were Lineage 2 and Lineage 4 respectively. The percentages of sub-lineage 2.2 (Beijing family strains) are significantly higher in hot spots. Through the MDS dimension reduction, the genomic population structure in the three hot spot counties is significantly different from those three cold spot counties (T-test p = 0.05). The median of SNPs distances among Mtb isolates in cold spots was greater than that in hot spots (897 vs 746, Rank-sum test p < 0.001). Three genomic clusters, each with genomic distance ≤ 12 SNPs, were identified with 2, 3 and 4 consanguineous strains. Two clusters were from hot spots and one was from cold spots.
Conclusion Narrower genotype diversity in the hot area may indicate higher transmissibility of the Mtb strains in the area compared to those in the cold spot area.
Figure 1
Figure 2
Figure 3
Figure 4