Molecular epidemiology of <i>Mycobacterium tuberculosis</i> in Brazil before the whole genome sequencing era: a literature review

Molecular-typing can help in unraveling epidemiological scenarios and improvement for disease control strategies. A literature review of Mycobacterium tuberculosis transmission in Brazil through genotyping on 56 studies published from 1996-2019 was performed. The clustering rate for mycobacterial interspersed repetitive units - variable tandem repeats (MIRU-VNTR) of 1,613 isolates were: 73%, 33% and 28% based on 12, 15 and 24-loci, respectively; while for RFLP-IS6110 were: 84% among prison population in Rio de Janeiro, 69% among multidrug-resistant isolates in Rio Grande do Sul, and 56.2% in general population in São Paulo. These findings could improve tuberculosis (TB) surveillance and set up a solid basis to build a database of Mycobacterium genomes.

Key words:
tuberculosis; Mycobacterium tuberculosis; genotyping; MIRU-VNTR typing; RFLP-IS6110; Brazil

Authorship

Emilyn Costa Conceição ⁺+ Corresponding author: emilyncosta@gmail.com

Fundação Oswaldo Cruz-Fiocruz, Instituto Nacional de Infectologia Evandro Chagas, Programa de Pós-Graduação em Pesquisa Clínica e Doenças Infecciosas, Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz-FiocruzBrazilRio de Janeiro, RJ, BrazilFundação Oswaldo Cruz-Fiocruz, Instituto Nacional de Infectologia Evandro Chagas, Programa de Pós-Graduação em Pesquisa Clínica e Doenças Infecciosas, Rio de Janeiro, RJ, Brasil

Fundação Oswaldo Cruz-Fiocruz, Instituto Nacional de Infectologia Evandro Chagas, Laboratório de Bacteriologia e Bioensaios em Micobactérias, Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz-FiocruzBrazilRio de Janeiro, RJ, BrazilFundação Oswaldo Cruz-Fiocruz, Instituto Nacional de Infectologia Evandro Chagas, Laboratório de Bacteriologia e Bioensaios em Micobactérias, Rio de Janeiro, RJ, Brasil

Fundação Oswaldo Cruz-Fiocruz, Instituto Oswaldo Cruz, Laboratório de Biologia Molecular Aplicada a Micobactérias, Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz-FiocruzBrazilRio de Janeiro, RJ, BrazilFundação Oswaldo Cruz-Fiocruz, Instituto Oswaldo Cruz, Laboratório de Biologia Molecular Aplicada a Micobactérias, Rio de Janeiro, RJ, Brasil

http://orcid.org/0000-0002-7445-6620

Richard Steiner Salvato

Universidade Federal do Rio Grande do Sul, Programa de Pós-Graduação em Biologia Celular e Molecular, Porto Alegre, RS, BrasilUniversidade Federal do Rio Grande do SulBrazilPorto Alegre, RS, BrazilUniversidade Federal do Rio Grande do Sul, Programa de Pós-Graduação em Biologia Celular e Molecular, Porto Alegre, RS, Brasil

Secretaria Estadual de Saúde do Rio Grande do Sul, Centro Estadual de Vigilância em Saúde, Centro de Desenvolvimento Científico e Tecnológico, Porto Alegre, RS, BrasilSecretaria Estadual de Saúde do Rio Grande do SulBrazilPorto Alegre, RS, BrazilSecretaria Estadual de Saúde do Rio Grande do Sul, Centro Estadual de Vigilância em Saúde, Centro de Desenvolvimento Científico e Tecnológico, Porto Alegre, RS, Brasil

Karen Machado Gomes

Fundação Oswaldo Cruz-Fiocruz, Escola Nacional de Saúde Pública Sergio Arouca, Centro de Referência Professor Hélio Fraga, Laboratório de Referência Nacional para Tuberculose e outras Micobacterioses, Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz-FiocruzBrazilRio de Janeiro, RJ, BrazilFundação Oswaldo Cruz-Fiocruz, Escola Nacional de Saúde Pública Sergio Arouca, Centro de Referência Professor Hélio Fraga, Laboratório de Referência Nacional para Tuberculose e outras Micobacterioses, Rio de Janeiro, RJ, Brasil

Arthur Emil dos Santos Guimarães

Universidade do Estado do Pará, Instituto de Ciências Biológicas e da Saúde, Pós-Graduação Biologia Parasitária na Amazônia, Belém, PA, BrasilUniversidade do Estado do ParáBrazilBelém, PA, BrazilUniversidade do Estado do Pará, Instituto de Ciências Biológicas e da Saúde, Pós-Graduação Biologia Parasitária na Amazônia, Belém, PA, Brasil

Instituto Evandro Chagas, Seção de Bacteriologia e Micologia, Ananindeua, PA, BrasilInstituto Evandro ChagasBrasilAnanindeua, PA, BrasilInstituto Evandro Chagas, Seção de Bacteriologia e Micologia, Ananindeua, PA, Brasil

Marília Lima da Conceição

Ricardo José de Paula Souza e Guimarães

Instituto Evandro Chagas, Laboratório de Geoprocessamento, Ananindeua, PA, BrasilInstituto Evandro ChagasBrasilAnanindeua, PA, BrasilInstituto Evandro Chagas, Laboratório de Geoprocessamento, Ananindeua, PA, Brasil

Abhinav Sharma

International Institute of Information Technology, Department of Data Science, Bangalore, IndiaInternational Institute of Information TechnologyIndiaBangalore, IndiaInternational Institute of Information Technology, Department of Data Science, Bangalore, India

Ismari Perini Furlaneto

Regina Bones Barcellos

Valdes Roberto Bollela

Universidade de São Paulo, Departamento de Clínica Médica da Faculdade de Medicina de Ribeirão Preto, Ribeirão Preto, SP, BrasilUniversidade de São PauloBrazilRibeirão Preto, SP, BrazilUniversidade de São Paulo, Departamento de Clínica Médica da Faculdade de Medicina de Ribeirão Preto, Ribeirão Preto, SP, Brasil

Lívia Maria Pala Anselmo

Maria Carolina Sisco

Universidade Federal do Rio de Janeiro, Instituto de Microbiologia Paulo de Góes, Laboratório de Micobactérias, Rio de Janeiro, RJ, BrasilUniversidade Federal do Rio de JaneiroBrazilRio de Janeiro, RJ, BrazilUniversidade Federal do Rio de Janeiro, Instituto de Microbiologia Paulo de Góes, Laboratório de Micobactérias, Rio de Janeiro, RJ, Brasil

Cristina Viana Niero

Universidade Federal de São Paulo, Departamento de Microbiologia, Imunologia e Parasitologia, São Paulo, SP, BrasilUniversidade Federal de São PauloBrazilSão Paulo, SP, BrazilUniversidade Federal de São Paulo, Departamento de Microbiologia, Imunologia e Parasitologia, São Paulo, SP, Brasil

Lucilaine Ferrazoli

Instituto Adolfo Lutz, Centro de Bacteriologia, Núcleo de Tuberculose e Micobacterioses, São Paulo, SP, BrasilInstituto Adolfo LutzBrazilSão Paulo, SP, BrazilInstituto Adolfo Lutz, Centro de Bacteriologia, Núcleo de Tuberculose e Micobacterioses, São Paulo, SP, Brasil

Guislaine Refrégier

Universit e Paris-Saclay, Ecologie Systematique Evolution, Centre National de la Recherche Scientifique, AgroParisTech, Orsay, FranceUniversit e Paris-SaclayFranceAgroParisTech, Orsay, FranceUniversit e Paris-Saclay, Ecologie Systematique Evolution, Centre National de la Recherche Scientifique, AgroParisTech, Orsay, France

Maria Cristina da Silva Lourenço

Harrison Magdinier Gomes

Artemir Coelho de Brito

Coordenação Geral de Vigilância das Doenças de Transmissão Respiratória de Condições Crônicas, Brasília, DF, BrasilCoordenação Geral de Vigilância das Doenças de Transmissão Respiratória de Condições CrônicasBrasilBrasília, DF, BrasilCoordenação Geral de Vigilância das Doenças de Transmissão Respiratória de Condições Crônicas, Brasília, DF, Brasil

Marcos Catanho

Fundação Oswaldo Cruz-Fiocruz, Instituto Oswaldo Cruz, Laboratório de Genética Molecular de Microrganismos, Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz-FiocruzBrazilRio de Janeiro, RJ, BrazilFundação Oswaldo Cruz-Fiocruz, Instituto Oswaldo Cruz, Laboratório de Genética Molecular de Microrganismos, Rio de Janeiro, RJ, Brasil

Rafael Silva Duarte

Philip Noel Suffys

Karla Valéria Batista Lima

+ Corresponding author: emilyncosta@gmail.com

PNS and KVBL contributed equally to supervising this work.

ECC conducted project conception and study designing, literature search, reviewed literature, data collection, data analysis, website conception, and was a major contributor in writing the manuscript; RSS, KMG, AESG, MLC, LMPA have performed the literature review, data-analysis, and manuscript edition; RJPSG performed the spatial analysis; IPF performed the statistical analysis; RBB provided epidemiological information from Brazilian database; AS contributed with literature search, writing the manuscript, and performed English review; MCS reviewed the manuscript writing and data-analysis; CVN, LF, MCSL and GR has contributed with their experience through manuscript edition and information regarding molecular techniques; VRB contributed writing the manuscript regarding his experience as a physician and the application of genotyping of MTBC; ACB contributed with information about the Brazilian structure of Tuberculosis program; MC developed the website for the whole-genome sequencing database; PNS, HMG, RSD and KVBL were the supervisors. All authors read and approved the final manuscript. The authors declare that they have no competing interests.

SCIMAGO INSTITUTIONS RANKINGS

Figures | Tables

Figures (4)
Tables (2)

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Fig. 1:
the Brazilian National System of Public Health Laboratories network classified by degree of complexity highlighting the two levels capable to elaborate a national genetic database for tuberculosis (TB) surveillance.

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Fig. 2:
the PRISMA flow diagram for each genotyping technique demonstrating the total of studies selected for this literature review: 1-A) mycobacterial interspersed repetitive unit-variable variable number tandem repeat (MIRU-VNTR) and 1-B) restriction fragment length polymorphism (RFLP-IS6110). 1-C) The 57 studies of Mycobacterium tuberculosis genotyping in Brazil and their distribution according to each method.

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Fig. 3:
studies distribution based on genotyping by restriction fragment length polymorphism (RFLP-IS6110) and mycobacterial interspersed repetitive unit-variable variable number tandem repeat (MIRU-VNTR) in Brazil. (A) Spatial localisation; (B) number of studies by states.

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Fig. 4:
minimum spanning trees (MST) demonstrating the genetic diversity of Mycobacterium tuberculosis in Brazil based on consideration of 12, 15 or 24 mycobacterial interspersed repetitive unit-variable variable number tandem repeat (MIRU-VNTR) alleles and considering a different dataset according to the method’s sampling. Samples are coloured according to state origin: Goiás (GO), Minas Gerais (MG), Rio de Janeiro (RJ), Rio Grande do Sul (RS), São Paulo (SP), and Pará (PA).

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TABLE I
Summary of restriction fragment length polymorphism-IS6110 (RFLP-IS6110) genotyping publications

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TABLE II
Clustering analysis of mycobacterial interspersed repetitive units - variable number tandem repeat (MIRU-VNTR)

Fig. 1: the Brazilian National System of Public Health Laboratories network classified by degree of complexity highlighting the two levels capable to elaborate a national genetic database for tuberculosis (TB) surveillance.

Fig. 2: the PRISMA flow diagram for each genotyping technique demonstrating the total of studies selected for this literature review: 1-A) mycobacterial interspersed repetitive unit-variable variable number tandem repeat (MIRU-VNTR) and 1-B) restriction fragment length polymorphism (RFLP-IS6110). 1-C) The 57 studies of Mycobacterium tuberculosis genotyping in Brazil and their distribution according to each method.

Fig. 3: studies distribution based on genotyping by restriction fragment length polymorphism (RFLP-IS6110) and mycobacterial interspersed repetitive unit-variable variable number tandem repeat (MIRU-VNTR) in Brazil. (A) Spatial localisation; (B) number of studies by states.

Fig. 4: minimum spanning trees (MST) demonstrating the genetic diversity of Mycobacterium tuberculosis in Brazil based on consideration of 12, 15 or 24 mycobacterial interspersed repetitive unit-variable variable number tandem repeat (MIRU-VNTR) alleles and considering a different dataset according to the method’s sampling. Samples are coloured according to state origin: Goiás (GO), Minas Gerais (MG), Rio de Janeiro (RJ), Rio Grande do Sul (RS), São Paulo (SP), and Pará (PA).

TABLE I Summary of restriction fragment length polymorphism-IS6110 (RFLP-IS6110) genotyping publications

	States	No. of studies^a	%	% by region	No. of IS6110	% in cluster
Southeast	SP	11	28.2	74.4	2 to 21	22 to 56
	ES	5	12.5		NR	40 to 48
	RJ	11	28.2		2 to 22	19 to 84^b
	MG	2	5.1		1 to 18	6 to 25
South	PR	0	0	10.3	-	-
	SC	0	0		-	-
	RS	4	10.3		1 to 18	36 to 69^c
Central West	GO	2	5.1	10.3	1 to 14	0
	MT	0	0		-	-
	MS	2	5.1		4 to 17	64 to 69^d
	DF	0	0		-	-
North	TO	0	0	2.6	-	-
	PA	0	0		-	-
	AP	0	0		-	-
	RR	1	2.6		NR	30
	AM	0	0		-	-
	RO	0	0		-	-
	AC	0	0		-	-
Northeast	MA	0	0	2.6	-	-
	PI	0	0		-	-
	CE	0	0		-	-
	RN	0	0		-	-
	PB	0	0		-	-
	PE	0	0		-	-
	AL	0	0		-	-
	SE	0	0		-	-
	BA	1	2.6		2 to 16	27
TOTAL		39	100	100	1 to 22	0 to 84

a: for these calculations, articles that analysed samples from more than one state in the same study were disregarded; b: study with inmate population; c: tuberculosis multidrug resistant (TB-MDR) population study; d: study with indigenous population; NR: not reported.

TABLE II Clustering analysis of mycobacterial interspersed repetitive units - variable number tandem repeat (MIRU-VNTR)

Typing methods	n	No. of different patterns	No. of clusters	No. of clusters isolates	No. of unique isolates	% in cluster	Size of clusters
MIRU-VNTR 12 loci	1,613	26	11	40	15	73%	2-7
MIRU-VNTR 15 loci	1,065	821	106	350	715	33%	2-23
MIRU-VNTR 24 loci	1,041	845	91	287	754	28%	2-11

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[1] + Corresponding author: emilyncosta@gmail.com