MIRU-profiler: a rapid tool for determination of 24-loci MIRU-VNTR profiles from assembled genomes of Mycobacterium tuberculosis

Introduction

Tuberculosis (TB) is an infectious disease responsible for an estimated 1.7 million deaths worldwide in the year 2016 alone (World Health Organization, 2017). In a global epidemic situation, genotyping of Mycobacterium tuberculosis complex strains (the causative agent of TB) is crucial for TB control particularly via epidemiological surveillance and monitoring TB-transmission.

The gold-standard method for genotyping M. tuberculosis has changed over time. In the 1990s, IS6110 restriction-fragment-length-polymorphism (RFLP) was recognized as the gold-standard for strain-discrimination and genotyping of M. tuberculosis (Otal et al., 1991). However, the laboratory procedure for IS6110-RFLP is time and labour-intensive. It requires large amount of pure DNA, which consequently requires weeks of bacterial cultivation. In 2001, mycobacterial-interspersed-repetitive-units (MIRU)-variable-number-of-tandem-repeats (VNTR) typing was developed, which is a polymerase-chain-reaction (PCR)-based method that could be performed on the crude DNA-extracts (Mazars et al., 2001).

The MIRU-VNTR typing examines polymorphisms in the number of repeat units at the selected VNTR-loci. The VNTRs are human minisatellite-like markers, that are composed of 50–100 bp repeat units, and are present at divergent locations on the genome. The laboratory procedure involves a PCR reaction with primers flanking the VNTR-loci and sizing of the PCR-amplicon subsequently. Since the length of the repeat unit is known, the number of copies of the repeat unit could be computed based on the PCR amplicon-size. Based on an analysis of over 800 clinical isolates from 28 countries, the discriminatory power for a set of 24 MIRU-VNTR loci was comparable to the previous gold standard genotyping method (i.e., IS6110-RFLP) (Supply et al., 2006). This standardization was performed by an international consortium, comprising of 11 European and American laboratories, which subsequently led to the establishment of 24-loci MIRU-VNTR typing as the new gold standard for genotyping M. tuberculosis, particularly for the routine epidemiological and phylogenetic analysis. The 24-loci MIRU-VNTR typing data is collected for all M. tuberculosis isolates by the public health laboratories in the Nordic countries (Denmark, Finland, Sweden), the Netherlands and the United Kingdom. Moreover, 21 European-Union/European-economic-area member-states also submit the genotyping data of at least 80% of the drug-resistant isolates to the European Centre for Disease Prevention and Control (ECDC) (ECDC, 2017). Since 2009, the United States (US)-CDC has implemented a nationwide program for 24-loci MIRU-VNTR typing of all M. tuberculosis isolates and has genotyped over 120,000 clinical strains already (CDC, 2008).

In the recent years, the whole-genome-sequencing (WGS) of M. tuberculosis has emerged as a molecular epidemiological tool. New reports have been published describing the applications of WGS for TB outbreak detection and investigating the direction of TB transmission (Folkvardsen et al., 2017; Satta et al., 2017; Shah et al., 2017). The WGS has the potential to distinguish between two strains differing by only a single nucleotide. It also reveals additional information related to drug-resistance and virulence. However, several obstacles yet remain before WGS could replace the current gold standard for M. tuberculosis genotyping (i.e., MIRU-VNTR typing). Foremost, defining a transmission cluster based on WGS is challenging. The preliminary studies have assigned M. tuberculosis strains to the same transmission-cluster if the genetic distance between them do not exceed five to twelve single nucleotide polymorphisms (SNPs) (Walker et al., 2013). However, this cut-off is expected to vary among human populations, sequencing platforms, bioinformatics pipelines, and phylogenetic lineage of the M. tuberculosis. A core-genome based multi-locus-sequence-typing is suggested as an alternative to the SNP-based clustering, however, a prospective evaluation of this approach on a large sample size is yet to be performed (Kohl et al., 2014). In brief, while WGS provides the highest resolution for epidemiological investigations, extensive standardization is required before its introduction into the clinical settings.

So far, fewer isolates have WGS data than MIRU-VNTR typing results. Over the past decade, MIRU-VNTR data has been collected for millions of isolates and are stored in public databases along with the detailed clinical and epidemiological information. As WGS is becoming more common for surveillance study, a bioinformatics tool is required to infer the MIRU-VNTR profiles from the genome sequences. This will facilitate an inter-laboratory communication between countries that have already implemented WGS and countries that use conventional MIRU-VNTR genotyping method.

In this report, an open-source bioinformatics tool “MIRU-profiler” is introduced, which predicts the standard 24-loci MIRU-VNTR profiles from multiple genome assemblies of M. tuberculosis in a single batch on any standard computer. The MIRU-profiler will facilitate effective linkage of genome-sequenced strains with MIRU-VNTR genotyped isolates, which has become critically important in the transitionary period of WGS as a routine epidemiological tool and continuous threats of TB outbreaks worldwide.

Materials and Methods

Construction and specification of the program

The MIRU-profiler is written in shell scripting language and is useful for digital genotyping M. tuberculosis strains based on standard 24-loci MIRU-VNTR. The program input is a FASTA file of whole-genome-sequence assembled using reads of 250 bp or longer. The MIRU-VNTR loci are not accurately assembled in genome assemblies with very short reads (for example 150 bp), therefore, assemblies based on them are not recommended as an input to the program (Table S1). The final output is the number of repeats at the 24 MIRU-VNTR loci in a tab-delimited text file for easy manipulation in spreadsheet editors (Microsoft Excel or LibreOffice Calc). The entire code is embedded in a loop which enables the program to accept multiple files as input and process them in a batch mode. Detailed installation and usage instructions are provided on the project homepage: https://github.com/rahimrajwani/MIRU-profiler. The in-silico workflow of the MIRU-profiler is similar to those recommended in previously published laboratory manuals (Supply, 2005) (Fig. 1).

First, standard PCR primers (Supply, 2005; Supply et al., 2006) are used to compute amplicon lengths for all 24 MIRU-VNTR loci in a given genome sequence using the EMBOSS primer search program (Rice, Longden & Bleasby, 2000). In order to account for the sequencing errors or polymorphisms within the primer sequences, the MIRU-profiler allows up to three mismatches (∼15%) within 20–24 nucleotides long primer sequences. In cases where multiple amplicons are detected, the amplicon resulting from the least number of mismatches within the primers, is further analyzed in the subsequent step. If an amplicon corresponding to a particular locus is not detected at all (either due to no hits for the primer, genomic deletion or absence of a corresponding contig), the program flags the locus as “NOT_DETECTED”.

Second, the number of repeats at the VNTR loci is computed based on amplicon-lengths as per the routinely used reference allele-calling table (Supply, 2005). At this step, the MIRU-profiler allows a user defined discrepancy range (in base-pairs) between the amplicon length in input sequence and the allele-calling table. If the amplicon-length range does not match with any number of repeats in the standard allele-calling table, the MIRU-profiler flags the locus as “UNKNOWN_ALLELE_NUM”. Under the default settings, the discrepancy range is set to ±5 bp to reduce the number of indeterminate loci without compromising the accuracy (Fig. S1).

The MIRU-profiler assumes that the source for the genome sequence is a pure culture from a single bacterial colony. Two alleles for the same locus (double alleles), which indicates mixed-culture or mixed-infection, are not reported by the MIRU-profiler. For detailed troubleshooting in case of “UNKNOWN_ALLELE_NUM” or “NOT_DETECTED”, MIRU-profiler generates an intermediate output file which describes the amplicon lengths for 24 MIRU-VNTR loci scanned in an input genome sequence.

Results

Evaluation on the genome assemblies based on the Illumina MiSeq data

The results of the MIRU-profiler evaluation on the genome assemblies based on 250 bp paired-end reads from the Illumina MiSeq machine are detailed in Table S3 and illustrated in Fig. 2. All 24-MIRU-VNTR loci were detected in 29/106 (27.3%) samples. A single locus was not detected in 45/106 (42.4%), two loci were not detected in 22/106 (20.7%) and three or more loci were not detected in the remaining 10/106 (9.4%) samples. Among all 106 samples, one specific locus (QUB26) was not detected in 65/106 (61.3%) samples, which could be due the inability of the genome assembly algorithm to assemble this locus with relatively long repeat length (111 bp). In a majority (78/106; 73.5%) of the samples, none of the 24-loci was flagged as the unknown allele number by the MIRU-profiler.

In comparison with the experimental results, there were 2/106 (1.8%) samples with no mismatches, 30/106 (28.3%) with a single mismatch, 29/106 (27.3%) with two mismatches and 45/106 (42.4%) with three or more mismatches. Among the 30 samples with a single mismatch, one specific locus (QUB11b) was discrepant in 86.6% (26/30) of the samples. Similarly, among the samples with two mismatches, one of the two discrepant loci was QUB11b and the other being QUB26 (44.8%; 13/29), ETRA (20.6%; 6/29), QUB4156 (20.6%; 6/29), MIRU10 (6.89; 2/29), Mtub29 (3.4%; 1/29) or Mtub21 (3.4%; 1/29). The high number of discrepancies for the QUB11b locus could be attributed to both errors in the genome assembly and experimental genotyping. The samples with a greater number of mismatches (three or more) were associated with reduced quality of the raw sequencing data and a higher number of assembled contigs. Overall, the number of samples with a mismatch for any given locus was not greater than 26/106 (25%) except for the ETRA (45/106;42.7%) and QUB11b (89/106; 83.9%).

The accuracy of the MIRU-profiler is dependent on the quality of the input assembly, which further depends on the quality of the raw sequencing data. The effect of the average sequencing depth on the detection of the MIRU-VNTR is illustrated in Fig. 2. The increase in sequencing depth from 5× to 20× increases the number of MIRU-VNTR loci detected. The increasing trend plateaus at 20×, suggesting a minimum of 20× sequencing depth is sufficient to detect all 24 loci, while a further increase in depth to 30× or more do not have any effect on the performance of the MIRU-profiler. The MIRU-profiler was also observed to be affected by the sequence quality of the raw reads and the number of contigs in the final assembly. Based on a ROC curve analysis, the average of the phred-scale quality scores for the sequencing reads should be at least 37 and the final assembly should be assembled into no more than 179 contigs to obtain a reliable digital MIRU-VNTR result with at most three mismatches (Table S3).

Thus, the MIRU-profiler could accurately infer the digital MIRU-VNTR results with at most three mismatches from assemblies based on the Illumina MiSeq 250 bp paired-end reads, given the sequence quality requirements are fulfilled.

Discussion

Here, we present the MIRU-profiler (a tool for digital MIRU-VNTR typing of M. tuberculosis) and evaluate its accuracy on four sets of experimentally genotyped and genome-sequenced strains, with widely different quality of genome assemblies. On all sets of M. tuberculosis strains, a good agreement between the MIRU-profiler and the experimental results was observed, which provides a confidence in in-silico inference of 24-loci MIRU-VNTR profiles from WGS using this tool. Other than M. tuberculosis, the MIRU-profiler also inferred accurate MIRU-VNTR profiles for the two BCG-vaccine strains, which indicates that the tool could possibly be applied to other members of the Mycobacterium tuberculosis complex, however, this must be further validated in the future.

The MIRU-profiler is the only available tool for digital MIRU-VNTR typing of multiple M. tuberculosis genomes, overcoming the limitations of existing tools for MIRU-VNTR analysis of M. tuberculosis. Previously available tools for MIRU-VNTR analysis do not offer an option to determine the 24-loci MIRU-VNTR profile from the genome sequence of M. tuberculosis or were limited in their throughput and accuracy. A recently developed web-based tool CASTB allows free service of digital MIRU-VNTR typing using assembled genome sequences (Iwai et al., 2015). However, the accuracy of the CASTB results was not compared with experimental results and it does not allow batch processing, which limits reliability and throughput of an analysis. In addition, unpublished genome sequences might need to be uploaded to the CASTB server, which raises further concerns about the data confidentiality. CASTB is also time inefficient. It requires uploading and downloading of data. Often, a request for analysis might need to be queued at the server-side before any results could be obtained. On the contrary, the MIRU-profiler results were compared to the experimental genotyping results in the current study. The MIRU-profiler is suitable for the bulk analysis of genome sequence data. It is more time efficient than the CASTB server, which is incapable of analyzing more than one genome at a time. The MIRU-profiler could be installed locally on any standard computer and the results could be obtained rapidly without any concerns on confidentiality.

Although the MIRU-profiler has several advantages such as the inference of digital MIRU-VNTR profiles from a large number of genomes in a single batch, some discrepancies were observed between the experimental and the digital MIRU-VNTR typing results. These discrepancies could be attributed to the errors in the interpretation of experimental results, microevolution or inaccuracies in the genome assembly. The experimental result is prone to errors due to sub-optimal PCR amplification, which results in multiple bands on an agarose gel electrophoresis and affects the interpretation of experimental results (Nikolayevskyy et al., 2016; Supply, 2005). The microevolution could also result in minor discrepancies between the experimental genotyping and WGS. Indeed, the most discrepant loci in our validation (QUB26 and QUB11b) were reported to be frequently associated with double alleles, a probable consequence of the microevolution (Jajou et al., 2017). The accuracy of the genome assembly, which crucially depends on the read length, is also vital to the digital inference of the MIRU-VNTR profile. The importance of a good quality genome assembly was quite evident from the validation results, where results nearly identical to the experimental genotyping were obtained for the complete genomes (e.g., locally isolated PacBio sequenced strains, BCG-vaccine strains and others downloaded from the NCBI-GenBank), while a few mismatches were observed for the genome assemblies based on Illumina MiSeq data. Nevertheless, even on the genome assemblies solely based on the Illumina MiSeq, at least 21/24 loci could be accurately inferred using the MIRU-profiler and the results for only three specific loci (QUB26, ETRA and QU11B) were unreliable due to the technological limitations. The current study validated the MIRU-profiler on the M. tuberculosis genomes assembled using reads 250 bp or longer, while a number of M. tuberculosis strains are currently also sequenced with reads 150 bp or shorter. The quality of the denovo assembly using relatively short reads (<150 bp) is rather low, particularly for the repetitive regions, therefore, genome assemblies based on reads 150 bp or shorter are inappropriate for the digital MIRU-VNTR analysis. The accuracy for the MIRU-profiler is best on the complete genomes assembled using long-read sequencing technologies (e.g., PacBio or Nanopore), with these technologies gradually becoming common in the clinical microbiology laboratories, the MIRU-profiler might be a useful solution to communicate with laboratories who may not have access to the WGS but perform MIRU-VNTR typing on a routine basis.

In conclusion, the MIRU-profiler is a rapid tool for the determination of MIRU-VNTR profiles from multiple assembled genome sequences of M. tuberculosis. The key features include fast computation, batch processing and data confidentiality. The accuracy of the MIRU-profiler is dependent on the quality of the input genome sequence. The results identical to the experimental typing could be obtained with high quality finished genomes. Thus, the MIRU-profiler might enable connections between the new genome sequenced isolates with a large number of unsequenced genotyped strains for epidemiological surveillance and research purposes.

Supplemental Information