- Open Access
A novel molecular typing method of Mycobacteria based on DNA barcoding visualization
© Liu et al.; licensee BioMed Central Ltd. 2014
Received: 13 January 2014
Accepted: 10 February 2014
Published: 20 February 2014
Different subtypes of Mycobacterium tuberculosis (MTB) may induce diverse severe human infections, and some of their symptoms are similar to other pathogenes, e.g. Nontuberculosis mycobacteria (NTM). So determination of mycobacterium subtypes facilitates the effective control of MTB infection and proliferation. This study exploits a novel DNA barcoding visualization method for molecular typing of 17 mycobacteria genomes published in the NCBI prokaryotic genome database. Three mycobacterium genes (Rv0279c, Rv3508 and Rv3514) from the PE/PPE family of MT Band were detected to best represent the inter-strain pathogenetic variations. An accurate and fast MTB substrain typing method was proposed based on the combination of the aforementioned three biomarker genes and the 16S rRNA gene. The protocol of establishing a bacterial substrain typing system used in this study may also be applied to the other pathogenes.
Nontuberculosis mycobacteria (NTM) are a diverse group of organisms that are ubiquitous in both natural and manmade environments . Though less notorious than Mycobacterium tuberculosis (MTB), NTM infections are also of clinical significance and have been associated with worldwide outbreaks in the past. A previous study showed that the clinical symptoms and iconography representation of NTM were similar to MTB making it difficult to differentiate between the two diseases. Furthermore, treatment is also more difficult because most of NTM are naturally resistant to anti-tuberculosis drugs . Thus, there is an urgent clinical need for tools that would enable accurate differentiation of MTB from NTM-induced disease. Since the genomes of different mycobacteria have been sequenced, it is now possible for us to generate a novel DNA barcoding technology for genotyping of mycobacteria.
Clinically, mycobacteria were traditionally characterized based on acid-fastness, smear and culture morphology, growth rate, pigment production and various biochemical tests . These parameters provide a useful tool to aid MTB diagnosis. However, a higher degree of differentiation, including the ability to distinguish between species and subspecies has become a requirement in both epidemiological and clinical settings. Thus, molecular based techniques could allow faster species identification and phylogenetic analyses. There are numerous published methods for mycobacteria genotyping, including insertion sequence (IS) 6110 restriction fragment length polymorphism (RFLP) analysis, PCR-based techniques, such as mycobacterial interspersed repetitive unit-variable number of tandem repeat (MIRU-VNTR) analysis, and so on. Despite the availability of all of these techniques, IS 6110-RELP has fallen out of favor because of cost and high quantities of purified genomic DNA requirements. Moreover, it is not applicable for trains with low copy numbers of IS6110 . Although MIRU-VNTR is accurate and effective in genotyping, however, to date, selection or choice of the mycobacterium-typing region is still problematic with considerable variation in the genotyping efficiency of different regions and lack of accuracy and uniformity . The underlying reasons for this could be ascribed to i) high conservation of mycobacteria nucleotide sequences and the low information content contained in simple sequence features; and ii) low distinguishability for the codon usage bias among different species, specific nucleotide distance and other biological characteristics.
We have previously shown that the frequency spectrum of each k-mer nucleotide string (K, 1 < K <6) within the region of equal length fragments in the microbial genome was consistent . It is therefore possible to obtain a barcode-like visual annotation (Barcode image) of a genome by constructing a digital and graphical process for the array matrix of the frequency spectrum. According to this hypothesis, any microbial genome can be represented as a unique barcode image. A genome barcode could carry all the genetic information in a given genome and exhibit a one-to-one correspondence with the genome sequence. Genome barcodes not only provide a useful tool to visualize any given genome, but also allows us to easily compare different genomes by calculating the whole genome k-mer average frequencies across the whole list of k-mers [7, 8].
In this study, we identified nucleotide fragments that contain both the genome barcode information and interspecific differences. We then utilized these fragments to perform genomic typing of mycobacteria. This study describes a novel tool that can be used to analyze different genomes leading to identification of subtypes of mycobacteria and can be implemented for future clinical use or epidemiological studies.
Materials and methods
Data on genome sequences of various types of mycobacteria
We downloaded the whole genomic sequences of 17 sequenced Mycobacterium strains from the NCBI database (http://www.ncbi.nlm.nih.gov/genome/) in January 2013. These data were used to construct DNA barcoding analyses.
Calculation of genomic barcode distance
Genomic barcode sectionalized identification method
Genotyping of mycobacteria
We first performed a blast search of the three screened genes using the NCBI blast tool (http://blast.ncbi.nlm.nih.gov/) E value set as 0 and the Max index value as ≥ 91%. We then utilized the ClustalX, jModelTest and MEGA (version 5.05) software s to molecularly type different types of mycobacterium.
Functional analysis of barcode genes via Pfam_Scan and Blast2GO
To functionally analyze the barcode genes, we first downloaded Pfam database version 23.0 from ftp://ftp.sanger.ac.uk/pub/databases/Pfam. The Pfam database mainly includes two parts, Pfam_ls and Pfam_fs. In this study, we mostly used the Pfam_ls component. Following this, we switched to the Pfam directory and ran hmmfam program to input the sequence data. Next, we analyzed the sequences through a GO annotating and functional analysis technology, $ hmmpfam --cpu 4 -E 0.0001 Pfam_ls InputSeq.fas > OutResults.fasBLAST2GO. We also used an online software Blast2GO (http://www.blast2go.de/) to annotate the genes, and set the E value as ≤ -10.
Genome barcode visual annotation of Mycobacterium
Screening of DNA barcoding genes base using distance of genomic barcode
Barcoding genes in the MTB H37Rv genome
PE-PGRS family protein
PE-PGRS family protein
PE-PGRS family protein
Phylogenetic analysis of mycobacteria based on barcoding genes
In the current study, we have generated a genomic barcode system using genome visualization technology and based on calculation of the base composition of mycobacterium genomes. We then identified three genes from mycobacterium genomes that have utility in genotyping mycobacteria. All of these three genes encoded proteins belonging to the PE-PGRS family, which is unique to MTB. Previous studies showed that single-nucleotide polymorphisms (SNPs) of most MTB genes occurred in the genomic region of the PE/PPE family [13, 14]. Functional analysis using Pfam database showed that Rv0279c participates in regulation of iron metabolism in the host [15, 16] while Rv3508 participates in oxidative stress [17, 18] and Rv3514 is a member of the cellular surface/secreted protein ESX family . These three genes are highly polymorphic and closely associated with the pathogenicity of MTB.
Evolutionary comparison between the various mycobacterial isolates revealed that the genetic distance between M. tuberculosis H37Rv and M. bovis BCG vaccine was quite close and therefore provides an explanation for the protective effects of M. bovis BCG vaccine. The genetic distance between Beijing strain CCDC5079, CCDC5180 and M. bovis BCG vaccine was relatively far. The two Beijing strains were isolated from tuberculosis patients in China in 2004 and are the main pandemic strains in China and other Asian countries, such as Japan, Korea, and India . The World Health Organization (WHO) reported that the protective rate of M. bovis BCG vaccine in North America and Northern Europe was among the highest (60%-80%), whereas there was no protective effect in the south of India (0%) because the pandemic strains in south of India was the Beijing strain. It is clear that our genomic barcode system can provide information on mycobacteria that is of biological significance and could help with the development of an effective vaccine.
The molecular phylogeny of mycobacterium showed that many NTMs have a close genetic distance with MTB. For example, the phylogenetic distance between M. marinum and MTB was very short, whereas the phylogenetic distance from M. avium was relatively long, which was confirmed by the whole genome sequence alignment analyses [21–23]. Our data showed that M. marinum and MTB had a closely genetic relationship with about 3000 homologous fragments between the two strains in addition to the amino acid being 85% (on average) identical. It is possible that the large genome of M. marinum allows it to adapt well to the environment and also enables this strain to be more pathogenic to a wide range of hosts. The nature and histologic characteristics of disease caused by M. marinum is surprisingly similar to that of MTB. This could be due to M. marinum possessing the same set of virulent genes as MTB [24, 25]. In conclusion, we propose that our novel gene barcode system is a useful tool in the molecular phylogenetic typing of mycobacteria.
In this report, we built a genomic barcode visualization technology through calculating the base composition of Mycobacterium, and screened three genes (Rv0279c, Rv3508 and Rv3514) from the PE/PPE family of MT Band which could be used in Mycobacterium typing. These three genes contained the whole genetic information of Mycobacterium, which had high distinguishability and combined with 16S rRNA gene could achieve accurate molecular typing. In the future, our genotyping research will support the genetic potentials accurately, and brings hope for conquer disease caused by mycobacterium.
This work was supported by National Natural Science Foundation of China (81101295 and 81271897), Specialized Research Fund for the Doctoral Program of Higher Education of China (20110061120093), China Postdoctoral Science Foundation (20110491311 and 2012T50285), Foundation of Jilin Provincial Health Department (2011Z049), Foundation of Jilin Province Science and Technology Department (20130522013JH and 20140414048GH)and the Norman Bethune Program of Jilin University (No. 2012219).
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