article information

Archives of Pediatric Infectious Diseases: Vol.5, issue 2; e40001
published online: October 16, 2016
article type: Research Article
received: June 23, 2016
revised: September 4, 2016
accepted: September 21, 2016
DOI: https://doi.org/10.5812/pedinfect.40001
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rpoB Gene Sequencing for Identification of Rapidly Growing Mycobacteria

authors:

avatar Mohammad Javad Nasiri 1 , avatar Abdolrazagh Hashemi Shahraki 2 , avatar Abbas Ali Imani Fooladi 3 , avatar Hossein Dabiri 1 , * , avatar Mohammad Mehdi Feizabadi 4

Department of Microbiology, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Department of Epidemiology, Pasteur Institute of Iran, Tehran, Iran
Applied Microbiology Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran
Department of Microbiology, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran

how to cite: Nasiri M J, Hashemi Shahraki A, Imani Fooladi A A, Dabiri H, Feizabadi M M. rpoB Gene Sequencing for Identification of Rapidly Growing Mycobacteria. Arch Pediatr Infect Dis. 2017;5(2):e40001. https://doi.org/10.5812/pedinfect.40001.

Abstract

Background:

Rapidly growing mycobacteria (RGM) are increasingly recognized as a cause of human infections. Rapid and reliable identification of RGM at species level should be carried out as a means of effective patient managements.

Methods:

Twenty clinical samples of RGM isolated from suspected tuberculosis (TB) patients were included. Different phenotypic tests and a hsp65-PCR restriction analysis (PRA) method were used to identify the isolated organisms to species level. Sequence analysis of the rpoB gene was also used for molecular identification of clinical isolates.

Results:

Phenotypic evaluation of clinical isolates assigned 19 (95%) isolates of RGM to M. fortuitum complex. Using hsp65-PRA, 13 isolates of M. fortuitum complex were identified as M. fortuitum, 4 isolates as M. abscessus and 1 isolates as M. chelonae. However, two isolates had identical hsp65-PRA patterns; one was indistinguishable from M. conceptionense and M. senegalense and another was indistinguishable from M. peregrinum and M. porcinum. By the rpoB gene sequence analysis, all species studied were readily discriminated from each other.

Conclusions:

rpoB gene sequencing has a high discriminatory power, which easily permits the identification of clinical isolates of RGM to the species level. It unambiguously differentiates between closely related species with restricted biochemical and PRA differences. This procedure is suggested as a first-line identification method for RGM.

1. Background

Rapidly growing mycobacteria (RGM) are increasingly recognized as a cause of human infections (1, 2). They are capable of causing serious illnesses such as pulmonary disease, skin and soft tissue infection and disseminated infection in both immunocompetent and immunocompromised individuals (3-5). This group of mycobacteria is heterogeneous in terms of epidemiology, clinical disease spectrum and drug sensitivity. It is therefore important to identify RGM to the species level (5-7). In most laboratories RGM identification currently relies on phenotypic tests. These phenotypic tests, however, are cumbersome and time-consuming and interpretation of the results is sometimes ambiguous. Phenotypic tests sometimes fail to discriminate between closely related species, such as Mycobacterium abscessus and Mycobacterium chelonae (8-10). Molecular tools including analyses of the 16S rRNA gene for the identification of mycobacteria have been developed in recent years (11-13). However, there is little variability within the mycobacterial 16S rRNA gene sequence in RGM, making this target a poor discriminator for closely related species (11, 12, 14). rpoB is a single-copy gene encoding the b-subunit of the bacterial RNA polymerase gene, which is present in all mycobacteria. It is more variable than the 16S rRNA gene sequence and is therefore potentially useful for the identification of genetically related species (1, 15). The aim of this work was to evaluate the potential of partial rpoB sequencing for the rapid identification of this group of emerging pathogens.

2. Methods

2.1. Mycobacterial Isolates

In this cross-sectional study, 20 clinical isolates of RGM collected by our clinical microbiology laboratory (Tehran reference laboratory) from January 2014 to December 2015 were included. They were isolated from sputum of suspected tuberculosis (TB) patients. If the patient had multiple longitudinal sampling, only the first set of samples was included into the study. The ethics committee of Shahid Beheshti University of Medical Sciences approved the study and all the patients have signed informed consent.

2.2. Phenotypic Identification

The clinical isolates were identified by conventional methods, i.e. growth rate, macroscopic and microscopic morphological features, growth at different temperatures, tween 80 hydrolysis, nitrate reduction, niacin production, arylsulfatase, urease production, tellurite reduction, salt tolerance and catalase production, according to standard procedures (16).

2.3. Restriction Analysis

PCR restriction analysis (PRA) was used to speciate mycobacteria. Genomic DNA was extracted using a QIAamp DNA Mini Kit (QIAGEN, USA). According to the kits instruction, for PRA, approximately 441 bp fragment of hsp65 gene was amplified by PCR using two specific primers Tb11 (50-ACCAACGATGGTGTGTCCAT-30) and Tb12 (50-CTTGTCGAACCGCATACCCT-30) (17). PCR products were digested with 5 U of restriction enzyme Hae III and Bst II for 24 hours at 37°C. The pattern of digested products was analyzed using 8% polyacrylamide gel. M. fortuitum (ATCC 49404) and double distilled water were used as positive and negative control in all PCR experiments, respectively. Species identification was performed using algorithm proposed by Chimara et al. (18).

2.4. PCR and Sequencing of rpoB Gene

As previously described, a 750 bp fragment of the rpoB gene was amplified and sequenced using two specific primers MycoF (50-GGCAAGGTCACCCCGAAGGG-30) and MycoR (50-AGCGGCTGCTGGGTGATCATC-30) (1). The obtained sequences for each isolate from different loci were aligned separately and compared with all existing relevant sequences of mycobacteria retrieved from the GenBank database at the NCBI website via the nucleotide BLAST search (http://blast.ncbi.nlm.nih.gov/Blast.cgi).

3. Results

3.1. Species Identification by Phenotypic Tests

On the basis of growth characteristics, the isolates studied were classified within the RGM group. According to phenotypic tests, 19 (95%) isolates assigned to the M. fortuitum complex and the one remaining isolate was unidentifiable (Table 1).

Table 1.

Results of RGM Identification by Phenotypic Tests

Numbers of IsolatesPhenotypic Characterization of Clinical IsolatesResult
Growth at 37°CGrowth at 42°CGrowth on MacConkey AgarUrease ProductionTween 80 HydrolysisPigment ProductionGrowth Rate (Days)Niacin ProductionNitrate ReductionHeat Stable CatalaseTellurite ReductionArylsulfatase (3 days)
13++++-N< 7-1++++M. fortuitum complex
4+-+++N< 7--+-+M. fortuitum complex
1+-+-+N< 7+++-+M. fortuitum complex
1+-+++N< 7-2++++M. fortuitum complex
1+-++-N< 7--+++Mycobacterium sp.

3.2. hsp65-PRA-Based Identification

According to hsp65-PRA results, an identical pattern was detected for the isolated microorganisms from each patient. Using hsp65-PRA, 13 isolates of M. fortuitum complex, which had been identified by phenotypic tests, were identified as M. fortuitum, 4 isolates as M. abscessus and 1 isolates as M. chelonae (Table 2). Thus, M. abscessus, formerly Mycobacterium chelonae subsp. abscessus, was easily distinguished from M. chelonae and M. fortuitum. Two isolates had identical hsp65-PRA patterns: one was indistinguishable from M. conceptionense and M. senegalense due to the same digestion pattern and another was indistinguishable from M. peregrinum and M. porcinum.

Table 2.

Results of RGM Identification by Genotypic Test and rpoB Sequencing

Numbers of IsolatesPhenotypic TestsPatterns by hsp65-PRAIdentification by PRAIdentification by rpoB Sequencing
Bst E IIHae III
13M. fortuitum complex235/120/85145/120/60/55M. fortuitumM. fortuitum
4M. fortuitum complex235/210145/70/60/55M. abscessusM. abscessus
1M. fortuitum complex235/210145/140/100/50M. peregrinum or M. porcinumM. porcinum
1M. fortuitum complex235/120/85140/125/60/55M. conceptionense or M. senegalenseM. senegalense
1Mycobacterium sp.320/130200/60/55/50M. chelonaeM. chelonae

3.3. Identification by rpoB Gene Sequencing

By using rpoB gene sequencing, all species studied were readily discriminated from each other. M. senegalense and M. porcinum, which could not be differentiated from closely related species by phenotypic and genotypic methods, were easily differentiated by rpoB sequencing (Table 2).

4. Discussion

There are increasing reports of nontuberculous mycobacterial (NTM) infection not only in the immunocompromised but also in immunocompetent. Amongst those species that are currently recognized, rapidly growing species such as M. fortuitum, M. chelonae and M. abscessus are frequently encountered and are clinically important (19). RGM are amongst the most common NTM isolate associated with nosocomial diseases (19). Previous studies demonstrated that tap water, processed tap water used for dialysis, as well as piped water systems in hospital settings are the usual nosocomial sources of NTM infections (19). Compared to M. tuberculosis, RGM are even more difficult to eradicate with common decontamination practices and are relatively resistant to standard anti-TB drugs (20, 21). Thus, transmission and spread of such NTM species from nosocomial sources may constitute the major part of the problem in hospital control strategies. As a result, rapid and reliable identification of RGM, at species level, should be carried out as a means of effective patient management and molecular epidemiology. PRA is one of the methods that is used and is simple and convenient (18, 22, 23). In the current study, phenotypic evaluation assigned 19 (95%) isolates to a species or complex. However, by the hsp65-PRA analysis, nearly all RGM isolates were accordingly speciated. Similar to our study, other reports from different parts of the world have shown that hsp65-PRA was significantly more accurate than the phenotypic methods (22-24). Nonetheless, the presence of unknown patterns as a result of gel-to-gel variation due to small restriction fragment sizes as well as identical patterns to that of M. conceptionense or M. senegalense based on the hsp65-PRA method emphasized the need for a more reliable identification method (16). rpoB gene sequencing is one of most common technique currently used for Mycobacterium species identification (15, 25). In comparison with hsp65-PRA, sequence analysis of rpoB can markedly improve molecular identification of clinical isolates. In this study, all clinical isolates were easily identified by using rpoB gene sequences analyses. The isolates belonging to closely related species such as M. conceptionense or M. senegalense and M. peregrinum or M. porcinum, which were poorly discriminated by the hsp65-PRA, were clearly delineated as M. senegalense and M. porcinum, respectively. This indicated that the hsp65-PRA was less discriminatory than the rpoB gene for RGM identification. This result was consistent with prior reports, which confirmed the high discriminatory power of the rpoB gene for species identification of RGM (15, 16).

In conclusion, rpoB gene sequencing has a high discriminatory power, which easily permits the identification of clinical isolates of RGM to the species level. It unambiguously differentiates between closely related species with restricted biochemical and PRA differences, such as M. conceptionense and M. senegalense. On the basis of the data presented here, we consider rpoB sequencing an appropriate identification method for RGM isolated from human samples.

Acknowledgements

References

  • 1.

    Adekambi T, Colson P, Drancourt M. rpoB-based identification of nonpigmented and late-pigmenting rapidly growing mycobacteria. J Clin Microbiol. 2003;41(12):5699-708. [PubMed ID: 14662964].

  • 2.

    Preece CL, Wichelhaus TA, Perry A, Jones AL, Cummings SP, Perry JD, et al. Evaluation of Various Culture Media for Detection of Rapidly Growing Mycobacteria from Patients with Cystic Fibrosis. J Clin Microbiol. 2016;54(7):1797-803. [PubMed ID: 27098962]. https://doi.org/10.1128/JCM.00471-16.

  • 3.

    Nasiri MJ, Dabiri H, Darban-Sarokhalil D, Hashemi Shahraki A. Prevalence of Non-Tuberculosis Mycobacterial Infections among Tuberculosis Suspects in Iran: Systematic Review and Meta-Analysis. PLoS One. 2015;10(6):e0129073. [PubMed ID: 26052701]. https://doi.org/10.1371/journal.pone.0129073.

  • 4.

    Rodriguez-Coste MA, Chirca I, Steed LL, Salgado CD. Epidemiology of Rapidly Growing Mycobacteria Bloodstream Infections. Am J Med Sci. 2016;351(3):253-8. [PubMed ID: 26992253]. https://doi.org/10.1016/j.amjms.2015.12.012.

  • 5.

    Lake MA, Ambrose LR, Lipman MC, Lowe DM. '"Why me, why now?" Using clinical immunology and epidemiology to explain who gets nontuberculous mycobacterial infection. BMC Med. 2016;14:54. [PubMed ID: 27007918]. https://doi.org/10.1186/s12916-016-0606-6.

  • 6.

    Raju RM, Raju SM, Zhao Y, Rubin EJ. Leveraging Advances in Tuberculosis Diagnosis and Treatment to Address Nontuberculous Mycobacterial Disease. Emerg Infect Dis. 2016;22(3):365-9. [PubMed ID: 26886068]. https://doi.org/10.3201/eid2203.151643.

  • 7.

    Andrews E, Marchand-Austin A, Sharma M, Brode SK, Marras TK, Jamieson FB. Nontuberculous Mycobacteria Drug Susceptibilities In Ontario, Canada, 2010-2015. Am Thoracic Soc; 2016.

  • 8.

    Tortoli E. Impact of genotypic studies on mycobacterial taxonomy: the new mycobacteria of the 1990s. Clin Microbiol Rev. 2003;16(2):319-54. [PubMed ID: 12692101].

  • 9.

    Scoleri GP, Choo JM, Leong LE, Goddard TR, Shephard L, Burr LD, et al. Culture-Independent Detection of Nontuberculous Mycobacteria in Clinical Respiratory Samples. J Clin Microbiol. 2016;54(9):2395-8. [PubMed ID: 27413194]. https://doi.org/10.1128/JCM.01410-16.

  • 10.

    Riello FN, Brigido RT, Araujo S, Moreira TA, Goulart LR, Goulart IM. Diagnosis of mycobacterial infections based on acid-fast bacilli test and bacterial growth time and implications on treatment and disease outcome. BMC Infect Dis. 2016;16:142. [PubMed ID: 27039183]. https://doi.org/10.1186/s12879-016-1474-6.

  • 11.

    Turenne CY, Tschetter L, Wolfe J, Kabani A. Necessity of quality-controlled 16S rRNA gene sequence databases: identifying nontuberculous Mycobacterium species. J Clin Microbiol. 2001;39(10):3637-48. [PubMed ID: 11574585]. https://doi.org/10.1128/JCM.39.10.3638-3648.2001.

  • 12.

    Tortoli E. Standard operating procedure for optimal identification of mycobacteria using 16S rRNA gene sequences. Stand Genomic Sci. 2010;3(2):145-52. [PubMed ID: 21304744]. https://doi.org/10.4056/sigs.932152.

  • 13.

    Joao I, Cristovao P, Antunes L, Nunes B, Jordao L. Identification of nontuberculous mycobacteria by partial gene sequencing and public databases. Int J Mycobacteriol. 2014;3(2):144-51. [PubMed ID: 26786337]. https://doi.org/10.1016/j.ijmyco.2014.04.001.

  • 14.

    Kim BJ, Lee SH, Lyu MA, Kim SJ, Bai GH, Chae GT, et al. Identification of mycobacterial species by comparative sequence analysis of the RNA polymerase gene (rpoB). J Clin Microbiol. 1999;37(6):1714-20. [PubMed ID: 10325313].

  • 15.

    de Zwaan R, van Ingen J, van Soolingen D. Utility of rpoB gene sequencing for identification of nontuberculous mycobacteria in the Netherlands. J Clin Microbiol. 2014;52(7):2544-51. [PubMed ID: 24808238]. https://doi.org/10.1128/JCM.00233-14.

  • 16.

    Hashemi-Shahraki A, Bostanabad SZ, Heidarieh P, Titov LP, Khosravi AD, Sheikhi N, et al. Species spectrum of nontuberculous mycobacteria isolated from suspected tuberculosis patients, identification by multi locus sequence analysis. Infect Genet Evol. 2013;20:312-24. [PubMed ID: 24070831]. https://doi.org/10.1016/j.meegid.2013.08.027.

  • 17.

    Telenti A, Marchesi F, Balz M, Bally F, Bottger EC, Bodmer T. Rapid identification of mycobacteria to the species level by polymerase chain reaction and restriction enzyme analysis. J Clin Microbiol. 1993;31(2):175-8. [PubMed ID: 8381805].

  • 18.

    Chimara E, Ferrazoli L, Ueky SY, Martins MC, Durham AM, Arbeit RD, et al. Reliable identification of mycobacterial species by PCR-restriction enzyme analysis (PRA)-hsp65 in a reference laboratory and elaboration of a sequence-based extended algorithm of PRA-hsp65 patterns. BMC Microbiol. 2008;8:48. [PubMed ID: 18366704]. https://doi.org/10.1186/1471-2180-8-48.

  • 19.

    De Groote MA, Huitt G. Infections due to rapidly growing mycobacteria. Clin Infect Dis. 2006;42(12):1756-63. [PubMed ID: 16705584]. https://doi.org/10.1086/504381.

  • 20.

    Griffith DE, Aksamit T, Brown-Elliott BA, Catanzaro A, Daley C, Gordin F, et al. An official ATS/IDSA statement: diagnosis, treatment, and prevention of nontuberculous mycobacterial diseases. Am J Respir Crit Care Med. 2007;175(4):367-416. [PubMed ID: 17277290]. https://doi.org/10.1164/rccm.200604-571ST.

  • 21.

    Brown-Elliott BA, Nash KA, Wallace RJ. Antimicrobial susceptibility testing, drug resistance mechanisms, and therapy of infections with nontuberculous mycobacteria. Clin Microbiol Rev. 2012;25(3):545-82. [PubMed ID: 22763637]. https://doi.org/10.1128/CMR.05030-11.

  • 22.

    Shojaei H, Heidarieh P, Hashemi A, Feizabadi MM, Daei Naser A. Species identification of neglected nontuberculous mycobacteria in a developing country. Jpn J Infect Dis. 2011;64(4):265-71. [PubMed ID: 21788699].

  • 23.

    Martin A, Uwizeye C, Fissette K, De Rijk P, Palomino JC, Leao S, et al. Application of the hsp65 PRA method for the rapid identification of mycobacteria isolated from clinical samples in Belgium. J Microbiol Methods. 2007;71(1):39-43. [PubMed ID: 17719666]. https://doi.org/10.1016/j.mimet.2007.07.008.

  • 24.

    Saifi M, Jabbarzadeh E, Bahrmand AR, Karimi A, Pourazar S, Fateh A, et al. HSP65-PRA identification of non-tuberculosis mycobacteria from 4892 samples suspicious for mycobacterial infections. Clin Microbiol Infect. 2013;19(8):723-8. [PubMed ID: 22963505]. https://doi.org/10.1111/j.1469-0691.2012.04005.x.

  • 25.

    Tortoli E. Phylogeny of the genus Mycobacterium: many doubts, few certainties. Infect Genet Evol. 2012;12(4):827-31. [PubMed ID: 21684354]. https://doi.org/10.1016/j.meegid.2011.05.025.