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Quan Z, Li M, Chen Y, Liang J, Takiff H, Gao Q. Performance evaluation of core genome multilocus sequence typing for genotyping of Mycobacterium tuberculosis strains in China: based on multicenter, population-based collection. Eur J Clin Microbiol Infect Dis 2024; 43:297-304. [PMID: 38041721 DOI: 10.1007/s10096-023-04720-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Accepted: 11/16/2023] [Indexed: 12/03/2023]
Abstract
PURPOSE To evaluate the performance of core genome multilocus sequence typing (cgMLST) for genotyping Mycobacterium tuberculosis (M.tuberculosis) Strains in regions where the lineage 2 strains predominate. METHODS We compared clustering by whole-genome SNP typing with cgMLST clustering in the analysis of WGS data of 6240 strains from five regions of China. Using both the receiver operating characteristic (ROC) curve and epidemiological investigation to determine the optimal threshold for defining genomic clustering by cgMLST. The performance of cgMLST was evaluated by quantifying the sensitivity, specificity and concordance of clustering between two methods. Logistic regression was used to gauge the impact of strain genetic diversity and lineage on cgMLST clustering. RESULTS The optimal threshold for cgMLST to define genomic clustering was determined to be ≤ 10 allelic differences between strains. The overall sensitivity and specificity of cgMLST averaged 99.6% and 96.3%, respectively; the concordance of clustering between two methods averaged 97.1%. Concordance was significantly correlated with strain genetic diversity and was 3.99 times (95% CI, 2.94-5.42) higher in regions with high genetic diversity (π > 1.55 × 10-4) compared to regions with low genetic diversity. The difference missed statistical significance, while concordance for lineage 2 strains (96.8%) was less than that for lineage 4 strains (98.3%). CONCLUSION : cgMLST showed a discriminatory power comparable to whole-genome SNP typing and could be used to genotype clinical M.tuberculosis strains in different regions of China. The discriminative power of cgMLST was significantly correlated with strain genetic diversity and was slightly lower with strains from regions with low genetic diversity.
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Affiliation(s)
- Zhuo Quan
- Shanghai Institute of Infectious Disease and Biosecurity, Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), School of Basic Medical Science, Fudan University, 131 Dongan Road, Shanghai, 200032, China
| | - Meng Li
- Shanghai Institute of Infectious Disease and Biosecurity, Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), School of Basic Medical Science, Fudan University, 131 Dongan Road, Shanghai, 200032, China
| | - Yiwang Chen
- Shanghai Institute of Infectious Disease and Biosecurity, Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), School of Basic Medical Science, Fudan University, 131 Dongan Road, Shanghai, 200032, China
| | - Jialei Liang
- Shanghai Institute of Infectious Disease and Biosecurity, Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), School of Basic Medical Science, Fudan University, 131 Dongan Road, Shanghai, 200032, China
| | - Howard Takiff
- Laboratorio de Genética Molecular, CMBC, Instituto Venezolano de Investigaciones Científicas, IVIC, Caracas, Venezuela
| | - Qian Gao
- Shanghai Institute of Infectious Disease and Biosecurity, Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), School of Basic Medical Science, Fudan University, 131 Dongan Road, Shanghai, 200032, China.
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Song Z, He W, Cao X, Ma A, He P, Zhao B, Wang S, Liu C, Zhao Y. The Recent Transmission and Associated Risk Factor of Mycobacterium tuberculosis in Golmud City, China. Infect Drug Resist 2024; 17:417-425. [PMID: 38318210 PMCID: PMC10840525 DOI: 10.2147/idr.s437026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Accepted: 12/05/2023] [Indexed: 02/07/2024] Open
Abstract
Background Tuberculosis (TB) remains a severe public health problem globally, and it is essential to comprehend the transmission pattern to control tuberculosis. Herein, we evaluated the drug-resistant characteristics, recent transmission, and associated risk factors of TB in Golmud, Qinghai, China. Methods In this study, we performed a population-based study of patients diagnosed with TB in Golmud from 2013 to 2018. Drug-susceptibility testing and whole-genome sequencing were performed on 133 Mycobacterium tuberculosis strains. The genomic clustering rate was calculated to evaluate the level of recent transmission. Risk factors were identified by logistic regression analysis. Results Our results showed that 46.97% (62/132) of strains were phylogenetically clustered and formed into 23 transmission clusters, suggesting a high recent transmission of TB in the area. 12.78% (17/133) strains were multidrug-resistant/rifampicin tuberculosis (MDR/RR-TB), with a high drug-resistant burden. Based on drug resistance gene analysis, we found 23 strains belonging to genotype MDR/RR-TB, where some strains may have borderline mutations. Among these strains, 65.2% (15/23) were found within putative transmission clusters. Additionally, risk factor analysis showed that recent transmission of TB happened more in patients with Tibetan nationality or older age. Conclusion Overall our study indicates that the recent transmissions of MTB strains, especially genotypic MDR/RR strains, drive the tuberculosis epidemic in Golmud, which could contribute to developing effective TB prevention and control strategies.
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Affiliation(s)
- Zexuan Song
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Changping, Beijing, 102206, People’s Republic of China
| | - Wencong He
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Changping, Beijing, 102206, People’s Republic of China
| | - Xiaolong Cao
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Changping, Beijing, 102206, People’s Republic of China
| | - Aijing Ma
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Changping, Beijing, 102206, People’s Republic of China
| | - Ping He
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Changping, Beijing, 102206, People’s Republic of China
| | - Bing Zhao
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Changping, Beijing, 102206, People’s Republic of China
| | - Shengfen Wang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Changping, Beijing, 102206, People’s Republic of China
| | - Chunfa Liu
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Changping, Beijing, 102206, People’s Republic of China
- Animal Science and Technology College, Beijing University of Agriculture, Huilongguan, Changping, Beijing, 102206, People’s Republic of China
| | - Yanlin Zhao
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Changping, Beijing, 102206, People’s Republic of China
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Mutayoba BK, Michael Hoelscher, Heinrich N, Joloba ML, Lyamuya E, Kilale AM, Range NS, Ngowi BJ, Ntinginya NE, Mfaume SM, Wilfred A, Doulla B, Lyimo J, Kisonga R, Kingalu A, Kabahita JM, Guido O, Kabugo J, Adam I, Luutu M, Namaganda MM, Namutebi J, Kasule GW, Nakato H, Byabajungu H, Lutaaya P, Musisi K, Oola D, Mboowa G, Pletschette M. Phylogenetic lineages of tuberculosis isolates and their association with patient demographics in Tanzania. BMC Genomics 2022; 23:561. [PMID: 35931954 PMCID: PMC9356438 DOI: 10.1186/s12864-022-08791-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Accepted: 07/12/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Mycobacterium tuberculosis presents several lineages each with distinct characteristics of evolutionary status, transmissibility, drug resistance, host interaction, latency, and vaccine efficacy. Whole genome sequencing (WGS) has emerged as a new diagnostic tool to reliably inform the occurrence of phylogenetic lineages of Mycobacterium tuberculosis and examine their relationship with patient demographic characteristics and multidrug-resistance development. METHODS 191 Mycobacterium tuberculosis isolates obtained from a 2017/2018 Tanzanian drug resistance survey were sequenced on the Illumina Miseq platform at Supranational Tuberculosis Reference Laboratory in Uganda. Obtained fast-q files were imported into tools for resistance profiling and lineage inference (Kvarq v0.12.2, Mykrobe v0.8.1 and TBprofiler v3.0.5). Additionally for phylogenetic tree construction, RaxML-NG v1.0.3(25) was used to generate a maximum likelihood phylogeny with 800 bootstrap replicates. The resulting trees were plotted, annotated and visualized using ggtree v2.0.4 RESULTS: Most [172(90.0%)] of the isolates were from newly treated Pulmonary TB patients. Coinfection with HIV was observed in 33(17.3%) TB patients. Of the 191 isolates, 22(11.5%) were resistant to one or more commonly used first line anti-TB drugs (FLD), 9(4.7%) isolates were MDR-TB while 3(1.6%) were resistant to all the drugs. Of the 24 isolates with any resistance conferring mutations, 13(54.2%) and 10(41.6%) had mutations in genes associated with resistance to INH and RIF respectively. The findings also show four major lineages i.e. Lineage 3[81 (42.4%)], followed by Lineage 4 [74 (38.7%)], the Lineage 1 [23 (12.0%)] and Lineages 2 [13 (6.8%)] circulaing in Tanzania. CONCLUSION The findings in this study show that Lineage 3 is the most prevalent lineage in Tanzania whereas drug resistant mutations were more frequent among isolates that belonged to Lineage 4.
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Affiliation(s)
- Beatrice Kemilembe Mutayoba
- Department of Preventive Services, Ministry of Health, Dodoma, Tanzania.
- Department of Infectious Diseases and Tropical Medicine, Medical Center of the, University of Munich, Munich, Germany.
| | - Michael Hoelscher
- Department of Infectious Diseases and Tropical Medicine, Medical Center of the, University of Munich, Munich, Germany
| | - Norbert Heinrich
- Department of Infectious Diseases and Tropical Medicine, Medical Center of the, University of Munich, Munich, Germany
| | - Moses L Joloba
- National Tuberculosis Reference Laboratory/Supranational Reference Laboratory, Luzira, Uganda
- Department of Immunology and Molecular Biology, College of Health Sciences, Makerere University, Kampala, Uganda
| | - Eligius Lyamuya
- Department of Microbiology and Immunology, Muhimbili University of Health and Allied Sciences (MUHAS), Dar es Salaam, Tanzania
| | - Andrew Martin Kilale
- Muhimbili Research Centre, National Institute for Medical Research (NIMR), Dar es Salaam, Tanzania
| | - Nyagosya Segere Range
- Muhimbili Research Centre, National Institute for Medical Research (NIMR), Dar es Salaam, Tanzania
| | - Bernard James Ngowi
- Muhimbili Research Centre, National Institute for Medical Research (NIMR), Dar es Salaam, Tanzania
- University of Dar Es Salaam, Mbeya College of Health and Allied Sciences, Mbeya, Tanzania
| | | | - Saidi Mwinjuma Mfaume
- Muhimbili Research Centre, National Institute for Medical Research (NIMR), Dar es Salaam, Tanzania
| | - Amani Wilfred
- Muhimbili Research Centre, National Institute for Medical Research (NIMR), Dar es Salaam, Tanzania
| | - Basra Doulla
- Central Tuberculosis Reference Laboratory, Ministry of Health, National TB and Leprosy Programme, Dar es Salaam, Tanzania
| | - Johnson Lyimo
- Department of Preventive Services, Ministry of Health, National Tuberculosis and Leprosy Programme, Dodoma, Tanzania
| | - Riziki Kisonga
- Department of Preventive Services, Ministry of Health, National Tuberculosis and Leprosy Programme, Dodoma, Tanzania
| | - Amri Kingalu
- Central Tuberculosis Reference Laboratory, Ministry of Health, National TB and Leprosy Programme, Dar es Salaam, Tanzania
| | - Jupiter Marina Kabahita
- National Tuberculosis Reference Laboratory/Supranational Reference Laboratory, Luzira, Uganda
| | - Ocung Guido
- National Tuberculosis Reference Laboratory/Supranational Reference Laboratory, Luzira, Uganda
| | - Joel Kabugo
- National Tuberculosis Reference Laboratory/Supranational Reference Laboratory, Luzira, Uganda
| | - Isa Adam
- National Tuberculosis Reference Laboratory/Supranational Reference Laboratory, Luzira, Uganda
| | - Moses Luutu
- Department of Immunology and Molecular Biology, College of Health Sciences, Makerere University, Kampala, Uganda
| | - Maria Magdalene Namaganda
- Department of Immunology and Molecular Biology, College of Health Sciences, Makerere University, Kampala, Uganda
| | - Joanitah Namutebi
- National Tuberculosis Reference Laboratory/Supranational Reference Laboratory, Luzira, Uganda
| | - George William Kasule
- National Tuberculosis Reference Laboratory/Supranational Reference Laboratory, Luzira, Uganda
| | - Hasfah Nakato
- National Tuberculosis Reference Laboratory/Supranational Reference Laboratory, Luzira, Uganda
| | - Henry Byabajungu
- National Tuberculosis Reference Laboratory/Supranational Reference Laboratory, Luzira, Uganda
| | - Pius Lutaaya
- National Tuberculosis Reference Laboratory/Supranational Reference Laboratory, Luzira, Uganda
| | - Kenneth Musisi
- National Tuberculosis Reference Laboratory/Supranational Reference Laboratory, Luzira, Uganda
| | - Denis Oola
- National Tuberculosis Reference Laboratory/Supranational Reference Laboratory, Luzira, Uganda
| | - Gerald Mboowa
- Africa Centres for Disease Control and Prevention, African Union Commission, Addis Ababa, Ethiopia
| | - Michel Pletschette
- Department of Infectious Diseases and Tropical Medicine, Medical Center of the, University of Munich, Munich, Germany
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Mudliar SKR, Kulsum U, Rufai SB, Umpo M, Nyori M, Singh S. Snapshot of Mycobacterium tuberculosis Phylogenetics from an Indian State of Arunachal Pradesh Bordering China. Genes (Basel) 2022. [DOI: https://doi.org/10.3390/genes13020263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Uncontrolled transmission of Mycobacterium tuberculosis (M. tuberculosis, MTB) drug resistant strains is a challenge to control efforts of the global tuberculosis program. Due to increasing multi-drug resistant (MDR) cases in Arunachal Pradesh, a northeastern state of India, the tracking and tracing of these resistant MTB strains is crucial for infection control and spread of drug resistance. This study aims to correlate the phenotypic DST, genomic DST (gDST) and phylogenetic analysis of MDR-MTB strains in the region. Of the total 200 samples 22 (11%) patients suspected of MDR-TB and 160 (80%) previously treated MDR-TB cases, 125 (62.5%) were identified as MTB. MGIT-960 SIRE DST detected 71/125 (56.8%) isolates as MDR/RR-MTB of which 22 (30.9%) were detected resistant to second-line drugs. Whole-genome sequencing of 65 isolates and their gDST found Ser315Thr mutation in katG (35/45; 77.8%) and Ser531Leu mutation in rpoB (21/41; 51.2%) associated with drug resistance. SNP barcoding categorized the dataset with Lineage2 (41; 63.1%) being predominant followed by Lineage3 (10; 15.4%), Lineage1 (8; 12.3%) and Lineage4 (6; 9.2%) respectively. Phylogenetic assignment by cgMLST gave insights of two Beijing sub-lineages viz; 2.2.1 (SNP difference < 19) and 2.2.1.2 (SNP difference < 9) associated with recent ongoing transmission in Arunachal Pradesh. This study provides insights in identifying two virulent Beijing sub-lineages (sub-lineage 2.2.1 and 2.2.1.2) with ongoing transmission of TB drug resistance in Arunachal Pradesh.
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Mudliar SKR, Kulsum U, Rufai SB, Umpo M, Nyori M, Singh S. Snapshot of Mycobacterium tuberculosis Phylogenetics from an Indian State of Arunachal Pradesh Bordering China. Genes (Basel) 2022. [DOI: https:/doi.org/10.3390/genes13020263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
Uncontrolled transmission of Mycobacterium tuberculosis (M. tuberculosis, MTB) drug resistant strains is a challenge to control efforts of the global tuberculosis program. Due to increasing multi-drug resistant (MDR) cases in Arunachal Pradesh, a northeastern state of India, the tracking and tracing of these resistant MTB strains is crucial for infection control and spread of drug resistance. This study aims to correlate the phenotypic DST, genomic DST (gDST) and phylogenetic analysis of MDR-MTB strains in the region. Of the total 200 samples 22 (11%) patients suspected of MDR-TB and 160 (80%) previously treated MDR-TB cases, 125 (62.5%) were identified as MTB. MGIT-960 SIRE DST detected 71/125 (56.8%) isolates as MDR/RR-MTB of which 22 (30.9%) were detected resistant to second-line drugs. Whole-genome sequencing of 65 isolates and their gDST found Ser315Thr mutation in katG (35/45; 77.8%) and Ser531Leu mutation in rpoB (21/41; 51.2%) associated with drug resistance. SNP barcoding categorized the dataset with Lineage2 (41; 63.1%) being predominant followed by Lineage3 (10; 15.4%), Lineage1 (8; 12.3%) and Lineage4 (6; 9.2%) respectively. Phylogenetic assignment by cgMLST gave insights of two Beijing sub-lineages viz; 2.2.1 (SNP difference < 19) and 2.2.1.2 (SNP difference < 9) associated with recent ongoing transmission in Arunachal Pradesh. This study provides insights in identifying two virulent Beijing sub-lineages (sub-lineage 2.2.1 and 2.2.1.2) with ongoing transmission of TB drug resistance in Arunachal Pradesh.
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Mudliar SKR, Kulsum U, Rufai SB, Umpo M, Nyori M, Singh S. Snapshot of Mycobacterium tuberculosis Phylogenetics from an Indian State of Arunachal Pradesh Bordering China. Genes (Basel) 2022; 13:genes13020263. [PMID: 35205308 PMCID: PMC8872330 DOI: 10.3390/genes13020263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Revised: 01/21/2022] [Accepted: 01/25/2022] [Indexed: 02/07/2023] Open
Abstract
Uncontrolled transmission of Mycobacterium tuberculosis (M. tuberculosis, MTB) drug resistant strains is a challenge to control efforts of the global tuberculosis program. Due to increasing multi-drug resistant (MDR) cases in Arunachal Pradesh, a northeastern state of India, the tracking and tracing of these resistant MTB strains is crucial for infection control and spread of drug resistance. This study aims to correlate the phenotypic DST, genomic DST (gDST) and phylogenetic analysis of MDR-MTB strains in the region. Of the total 200 samples 22 (11%) patients suspected of MDR-TB and 160 (80%) previously treated MDR-TB cases, 125 (62.5%) were identified as MTB. MGIT-960 SIRE DST detected 71/125 (56.8%) isolates as MDR/RR-MTB of which 22 (30.9%) were detected resistant to second-line drugs. Whole-genome sequencing of 65 isolates and their gDST found Ser315Thr mutation in katG (35/45; 77.8%) and Ser531Leu mutation in rpoB (21/41; 51.2%) associated with drug resistance. SNP barcoding categorized the dataset with Lineage2 (41; 63.1%) being predominant followed by Lineage3 (10; 15.4%), Lineage1 (8; 12.3%) and Lineage4 (6; 9.2%) respectively. Phylogenetic assignment by cgMLST gave insights of two Beijing sub-lineages viz; 2.2.1 (SNP difference < 19) and 2.2.1.2 (SNP difference < 9) associated with recent ongoing transmission in Arunachal Pradesh. This study provides insights in identifying two virulent Beijing sub-lineages (sub-lineage 2.2.1 and 2.2.1.2) with ongoing transmission of TB drug resistance in Arunachal Pradesh.
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Affiliation(s)
- Shiv kumar Rashmi Mudliar
- Department of Microbiology, All India Institute of Medical Sciences, Bhopal 462020, Madhya Pradesh, India; (S.k.R.M.); (U.K.)
| | - Umay Kulsum
- Department of Microbiology, All India Institute of Medical Sciences, Bhopal 462020, Madhya Pradesh, India; (S.k.R.M.); (U.K.)
| | - Syed Beenish Rufai
- Infectious Diseases and Immunity in Global Health Program, Research Institute of the McGill University Health Center, Montreal, QC H4A 3J1, Canada;
- McGill International TB Center, Montreal, QC H4A 3J1, Canada
| | - Mika Umpo
- Tomo Riba Institute of Health & Medical Sciences, Naharlagun 791110, Arunachal Pradesh, India;
| | - Moi Nyori
- State TB Cell, Naharlagun 791110, Arunachal Pradesh, India;
| | - Sarman Singh
- Department of Microbiology, All India Institute of Medical Sciences, Bhopal 462020, Madhya Pradesh, India; (S.k.R.M.); (U.K.)
- Correspondence: ; Tel.: +91-9810813435
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Di Pasquale A, Radomski N, Mangone I, Calistri P, Lorusso A, Cammà C. SARS-CoV-2 surveillance in Italy through phylogenomic inferences based on Hamming distances derived from pan-SNPs, -MNPs and -InDels. BMC Genomics 2021; 22:782. [PMID: 34717546 PMCID: PMC8556844 DOI: 10.1186/s12864-021-08112-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Accepted: 10/20/2021] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND Faced with the ongoing global pandemic of coronavirus disease, the 'National Reference Centre for Whole Genome Sequencing of microbial pathogens: database and bioinformatic analysis' (GENPAT) formally established at the 'Istituto Zooprofilattico Sperimentale dell'Abruzzo e del Molise' (IZSAM) in Teramo (Italy) is in charge of the SARS-CoV-2 surveillance at the genomic scale. In a context of SARS-CoV-2 surveillance requiring correct and fast assessment of epidemiological clusters from substantial amount of samples, the present study proposes an analytical workflow for identifying accurately the PANGO lineages of SARS-CoV-2 samples and building of discriminant minimum spanning trees (MST) bypassing the usual time consuming phylogenomic inferences based on multiple sequence alignment (MSA) and substitution model. RESULTS GENPAT constituted two collections of SARS-CoV-2 samples. The first collection consisted of SARS-CoV-2 positive swabs collected by IZSAM from the Abruzzo region (Italy), then sequenced by next generation sequencing (NGS) and analyzed in GENPAT (n = 1592), while the second collection included samples from several Italian provinces and retrieved from the reference Global Initiative on Sharing All Influenza Data (GISAID) (n = 17,201). The main results of the present work showed that (i) GENPAT and GISAID detected the same PANGO lineages, (ii) the PANGO lineages B.1.177 (i.e. historical in Italy) and B.1.1.7 (i.e. 'UK variant') are major concerns today in several Italian provinces, and the new MST-based method (iii) clusters most of the PANGO lineages together, (iv) with a higher dicriminatory power than PANGO lineages, (v) and faster that the usual phylogenomic methods based on MSA and substitution model. CONCLUSIONS The genome sequencing efforts of Italian provinces, combined with a structured national system of NGS data management, provided support for surveillance SARS-CoV-2 in Italy. We propose to build phylogenomic trees of SARS-CoV-2 variants through an accurate, discriminant and fast MST-based method avoiding the typical time consuming steps related to MSA and substitution model-based phylogenomic inference.
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Affiliation(s)
- Adriano Di Pasquale
- National Reference Centre (NRC) for Whole Genome Sequencing of microbial pathogens: data-base and bioinformatics analysis (GENPAT), Istituto Zooprofilattico Sperimentale dell’Abruzzo e del Molise “Giuseppe Caporale” (IZSAM), via Campo Boario, 64100 Teramo, TE Italy
| | - Nicolas Radomski
- National Reference Centre (NRC) for Whole Genome Sequencing of microbial pathogens: data-base and bioinformatics analysis (GENPAT), Istituto Zooprofilattico Sperimentale dell’Abruzzo e del Molise “Giuseppe Caporale” (IZSAM), via Campo Boario, 64100 Teramo, TE Italy
| | - Iolanda Mangone
- National Reference Centre (NRC) for Whole Genome Sequencing of microbial pathogens: data-base and bioinformatics analysis (GENPAT), Istituto Zooprofilattico Sperimentale dell’Abruzzo e del Molise “Giuseppe Caporale” (IZSAM), via Campo Boario, 64100 Teramo, TE Italy
| | - Paolo Calistri
- National Reference Centre (NRC) for Whole Genome Sequencing of microbial pathogens: data-base and bioinformatics analysis (GENPAT), Istituto Zooprofilattico Sperimentale dell’Abruzzo e del Molise “Giuseppe Caporale” (IZSAM), via Campo Boario, 64100 Teramo, TE Italy
| | - Alessio Lorusso
- National Reference Centre (NRC) for Whole Genome Sequencing of microbial pathogens: data-base and bioinformatics analysis (GENPAT), Istituto Zooprofilattico Sperimentale dell’Abruzzo e del Molise “Giuseppe Caporale” (IZSAM), via Campo Boario, 64100 Teramo, TE Italy
| | - Cesare Cammà
- National Reference Centre (NRC) for Whole Genome Sequencing of microbial pathogens: data-base and bioinformatics analysis (GENPAT), Istituto Zooprofilattico Sperimentale dell’Abruzzo e del Molise “Giuseppe Caporale” (IZSAM), via Campo Boario, 64100 Teramo, TE Italy
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Liang KYH, Orata FD, Islam MT, Nasreen T, Alam M, Tarr CL, Boucher YF. A Vibrio cholerae Core Genome Multilocus Sequence Typing Scheme To Facilitate the Epidemiological Study of Cholera. J Bacteriol 2020; 202:e00086-20. [PMID: 32540931 PMCID: PMC7685551 DOI: 10.1128/jb.00086-20] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2020] [Accepted: 06/07/2020] [Indexed: 12/11/2022] Open
Abstract
Core genome multilocus sequence typing (cgMLST) has gained popularity in recent years in epidemiological research and subspecies-level classification. cgMLST retains the intuitive nature of traditional MLST but offers much greater resolution by utilizing significantly larger portions of the genome. Here, we introduce a cgMLST scheme for Vibrio cholerae, a bacterium abundant in marine and freshwater environments and the etiologic agent of cholera. A set of 2,443 core genes ubiquitous in V. cholerae were used to analyze a comprehensive data set of 1,262 clinical and environmental strains collected from 52 countries, including 65 newly sequenced genomes in this study. We established a sublineage threshold based on 133 allelic differences that creates clusters nearly identical to traditional MLST types, providing backwards compatibility to new cgMLST classifications. We also defined an outbreak threshold based on seven allelic differences that is capable of identifying strains from the same outbreak and closely related isolates that could give clues on outbreak origin. Using cgMLST, we confirmed the South Asian origin of modern epidemics and identified clustering affinity among sublineages of environmental isolates from the same geographic origin. Advantages of this method are highlighted by direct comparison with existing classification methods, such as MLST and single-nucleotide polymorphism-based methods. cgMLST outperforms all existing methods in terms of resolution, standardization, and ease of use. We anticipate this scheme will serve as a basis for a universally applicable and standardized classification system for V. cholerae research and epidemiological surveillance in the future. This cgMLST scheme is publicly available on PubMLST (https://pubmlst.org/vcholerae/).IMPORTANCE Toxigenic Vibrio cholerae isolates of the O1 and O139 serogroups are the causative agents of cholera, an acute diarrheal disease that plagued the world for centuries, if not millennia. Here, we introduce a core genome multilocus sequence typing scheme for V. cholerae Using this scheme, we have standardized the definition for subspecies-level classification, facilitating global collaboration in the surveillance of V. cholerae In addition, this typing scheme allows for quick identification of outbreak-related isolates that can guide subsequent analyses, serving as an important first step in epidemiological research. This scheme is also easily scalable to analyze thousands of isolates at various levels of resolution, making it an invaluable tool for large-scale ecological and evolutionary analyses.
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Affiliation(s)
- Kevin Y H Liang
- Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada
| | - Fabini D Orata
- Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada
| | | | - Tania Nasreen
- Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada
| | - Munirul Alam
- Infectious Diseases Division, International Centre for Diarrhoeal Disease Research, Dhaka, Bangladesh
| | - Cheryl L Tarr
- Enteric Diseases Laboratory Branch, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Yann F Boucher
- Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
- Singapore Center for Environmental Life Sciences Engineering, National University of Singapore, Singapore, Singapore
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Bitar I, Medvecky M, Amlerova J, Papagiannitsis CC, Hrabak J. Frequency of mutations associated with resistance to first- and second-line drugs in multidrug-resistant Mycobacterium tuberculosis isolates. J Glob Antimicrob Resist 2020; 22:275-282. [PMID: 32247078 DOI: 10.1016/j.jgar.2020.03.013] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Revised: 02/27/2020] [Accepted: 03/14/2020] [Indexed: 01/19/2023] Open
Abstract
INTRODUCTION Tuberculosis is considered one of the most fatal diseases worldwide, with an estimation of 10.1 million cases. In this study, whole-genome sequencing was used to determine the genomic characterisation of 40 Mycobacterium tuberculosis isolates from patients with different nationalities hospitalised in the Czech Republic. MATERIALS AND METHODS Susceptibility testing for first-line drugs was performed. DNA was sequenced using the Illumina MiSeq platform. Spoligotype single-nucleotide polymorphisms and mutations in antibiotic-resistant genes were detected, and phylogenetic analysis was performed. RESULTS Samples showing phenotypic resistance to at least one drug were 12 to streptomycin, 11 to isoniazid, 7 to rifampicin, 6 to ethambutol and 5 to pyrazinamide. Phenotypic and genotypic profiles did not match in all cases, suggesting the presence of a novel mutation in some cases and a low expression of resistant genes in others. The presented phylogeny enables the correct assignation of M. tuberculosis lineages and sublineages. Our results suggest that the most dominant lineage in our samples was lineage 4 (33/40). CONCLUSION To our knowledge, this is the first study using this approach to be done in the Czech Republic. Lineage 4 was the predominant lineage identified among our samples. Nevertheless, the dominance of Lineage 4 along with other lineages suggests that infections can originate from different sources.
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Affiliation(s)
- Ibrahim Bitar
- Department of Microbiology, Faculty of Medicine in Pilsen, Charles University, Plzen, Czech Republic; Biomedical Center, Faculty of Medicine in Pilsen, Charles University, Plzen, Czech Republic.
| | - Matej Medvecky
- Biomedical Center, Faculty of Medicine in Pilsen, Charles University, Plzen, Czech Republic; CEITEC VFU, University of Veterinary and Pharmaceutical Sciences Brno, Brno, Czech Republic
| | - Jana Amlerova
- Department of Microbiology, Faculty of Medicine in Pilsen, Charles University, Plzen, Czech Republic; Biomedical Center, Faculty of Medicine in Pilsen, Charles University, Plzen, Czech Republic
| | - Costas C Papagiannitsis
- Department of Microbiology, Faculty of Medicine in Pilsen, Charles University, Plzen, Czech Republic; Biomedical Center, Faculty of Medicine in Pilsen, Charles University, Plzen, Czech Republic
| | - Jaroslav Hrabak
- Department of Microbiology, Faculty of Medicine in Pilsen, Charles University, Plzen, Czech Republic; Biomedical Center, Faculty of Medicine in Pilsen, Charles University, Plzen, Czech Republic
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Cui Z, Lin D, Chongsuvivatwong V, Graviss EA, Chaiprasert A, Palittapongarnpim P, Lin M, Ou J, Zhao J. Hot and Cold Spot Areas of Household Tuberculosis Transmission in Southern China: Effects of Socio-Economic Status and Mycobacterium tuberculosis Genotypes. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2019; 16:ijerph16101863. [PMID: 31137811 PMCID: PMC6572207 DOI: 10.3390/ijerph16101863] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/19/2019] [Revised: 05/19/2019] [Accepted: 05/23/2019] [Indexed: 11/16/2022]
Abstract
The aims of the study were: (1) compare sociodemographic characteristics among active tuberculosis (TB) cases and their household contacts in cold and hot spot transmission areas, and (2) quantify the influence of locality, genotype and potential determinants on the rates of latent tuberculosis infection (LTBI) among household contacts of index TB cases. Parallel case-contact studies were conducted in two geographic areas classified as "cold" and "hot" spots based on TB notification and spatial clustering between January and June 2018 in Guangxi, China, using data from field contact investigations, whole genome sequencing, tuberculin skin tests (TSTs), and chest radiographs. Beijing family strains accounted for 64.6% of Mycobacterium tuberculosis (Mtb) strains transmitted in hot spots, and 50.7% in cold spots (p-value = 0.02). The positive TST rate in hot spot areas was significantly higher than that observed in cold spot areas (p-value < 0.01). Living in hot spots (adjusted odds ratio (aOR) = 1.75, 95%, confidence interval (CI): 1.22, 2.50), Beijing family genotype (aOR = 1.83, 95% CI: 1.19, 2.81), living in the same room with an index case (aOR = 2.29, 95% CI: 1.5, 3.49), travelling time from home to a medical facility (aOR = 4.78, 95% CI: 2.96, 7.72), history of Bacillus Calmette-Guérin vaccination (aOR = 2.02, 95% CI: 1.13 3.62), and delay in diagnosis (aOR = 2.56, 95% CI: 1.13, 5.80) were significantly associated with positive TST results among household contacts of TB cases. The findings of this study confirmed the strong transmissibility of the Beijing genotype family strains and this genotype's important role in household transmission. We found that an extended traveling time from home to the medical facility was an important socioeconomic factor for Mtb transmission in the family. It is still necessary to improve the medical facility infrastructure and management, especially in areas with a high TB prevalence.
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Affiliation(s)
- Zhezhe Cui
- Department of Tuberculosis Control, Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning 530028, China.
- Epidemiology Unit, Faculty of Medicine, Prince of Songkla University, Songkhla 90110, Thailand.
| | - Dingwen Lin
- Department of Tuberculosis Control, Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning 530028, China.
| | | | - Edward A Graviss
- Department of Pathology and Genomic Medicine, The Center for Molecular and Translational Human Infectious Diseases Research, Houston Methodist Research Institute, Houston, TX 77030, USA.
| | - Angkana Chaiprasert
- Office for Research and Development, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand.
| | | | - Mei Lin
- Department of Tuberculosis Control, Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning 530028, China.
| | - Jing Ou
- Department of Tuberculosis Control, Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning 530028, China.
| | - Jinming Zhao
- Department of Tuberculosis Control, Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning 530028, China.
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