Generalist and specialist species differ in the breadth of their ecological niche. Little is known about the niche width of obligate human pathogens. Here we analyzed a global collection of Mycobacterium tuberculosis Lineage 4 clinical isolates, the most geographically widespread cause of human tuberculosis. We show that Lineage 4 comprises globally distributed and geographically restricted sublineages, suggesting a distinction between generalists and specialists. Population genomic analyses showed that while the majority of human T cell epitopes were conserved in all sublineages, the proportion of variable epitopes was higher in generalists. Our data further support a European origin for the most common generalist sublineage. Hence, the global success of Lineage 4 reflects distinct strategies adopted by different sublineages and the influence of human migration.

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BackgroundHigh-throughput DNA sequencing produces vast amounts of data, with millions of short reads that usually have to be mapped to a reference genome or newly assembled. Both reference-based mapping and de novo assembly are computationally intensive, generating large intermediary data files, and thus require bioinformatics skills that are often lacking in the laboratories producing the data. Moreover, many research and practical applications in microbiology require only a small fraction of the whole genome data.ResultsWe developed KvarQ, a new tool that directly scans fastq files of bacterial genome sequences for known variants, such as single nucleotide polymorphisms (SNP), bypassing the need of mapping all sequencing reads to a reference genome and de novo assembly. Instead, KvarQ loads “testsuites” that define specific SNPs or short regions of interest in a reference genome, and directly synthesizes the relevant results based on the occurrence of these markers in the fastq files. KvarQ has a versatile command line interface and a graphical user interface. KvarQ currently ships with two “testsuites” for Mycobacterium tuberculosis, but new “testsuites” for other organisms can easily be created and distributed. In this article, we demonstrate how KvarQ can be used to successfully detect all main drug resistance mutations and phylogenetic markers in 880 bacterial whole genome sequences. The average scanning time per genome sequence was two minutes. The variant calls of a subset of these genomes were validated with a standard bioinformatics pipeline and revealed >99% congruency.ConclusionKvarQ is a user-friendly tool that directly extracts relevant information from fastq files. This enables researchers and laboratory technicians with limited bioinformatics expertise to scan and analyze raw sequencing data in a matter of minutes. KvarQ is open-source, and pre-compiled packages with a graphical user interface are available at http://www.swisstph.ch/kvarq.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-15-881) contains supplementary material, which is available to authorized users.

There is increasing evidence that strain variation in Mycobacterium tuberculosis complex (MTBC) might influence the outcome of tuberculosis infection and disease. To assess genotype-phenotype associations, phylogenetically robust molecular markers and appropriate genotyping tools are required. Most current genotyping methods for MTBC are based on mobile or repetitive DNA elements. Because these elements are prone to convergent evolution, the corresponding genotyping techniques are suboptimal for phylogenetic studies and strain classification. By contrast, single nucleotide polymorphisms (SNP) are ideal markers for classifying MTBC into phylogenetic lineages, as they exhibit very low degrees of homoplasy. In this study, we developed two complementary SNP-based genotyping methods to classify strains into the six main human-associated lineages of MTBC, the “Beijing” sublineage, and the clade comprising Mycobacterium bovis and Mycobacterium caprae . Phylogenetically informative SNPs were obtained from 22 MTBC whole-genome sequences. The first assay, referred to as MOL-PCR, is a ligation-dependent PCR with signal detection by fluorescent microspheres and a Luminex flow cytometer, which simultaneously interrogates eight SNPs. The second assay is based on six individual TaqMan real-time PCR assays for singleplex SNP-typing. We compared MOL-PCR and TaqMan results in two panels of clinical MTBC isolates. Both methods agreed fully when assigning 36 well-characterized strains into the main phylogenetic lineages. The sensitivity in allele-calling was 98.6% and 98.8% for MOL-PCR and TaqMan, respectively. Typing of an additional panel of 78 unknown clinical isolates revealed 99.2% and 100% sensitivity in allele-calling, respectively, and 100% agreement in lineage assignment between both methods. While MOL-PCR and TaqMan are both highly sensitive and specific, MOL-PCR is ideal for classification of isolates with no previous information, whereas TaqMan is faster for confirmation. Furthermore, both methods are rapid, flexible and comparably inexpensive.

The degree to which a water sample can potentially support the growth of human pathogens was evaluated. For this purpose, a pathogen growth potential (PGP) bioassay was developed based on the principles of conventional assimilable organic carbon (AOC) determination, but using pure cultures of selected pathogenic bacteria (Escherichia coli O157, Vibrio cholerae, or Pseudomonas aeruginosa) as the inoculum. We evaluated 19 water samples collected after different treatment steps from two drinking water production plants and a wastewater treatment plant and from ozone-treated river water. Each pathogen was batch grown to stationary phase in sterile water samples, and the concentration of cells produced was measured using flow cytometry. In addition, the fraction of AOC consumed by each pathogen was estimated. Pathogen growth did not correlate with dissolved organic carbon (DOC) concentration and correlated only weakly with the concentration of AOC. Furthermore, the three pathogens never grew to the same final concentration in any water sample, and the relative ratio of the cultures to each other was unique in each sample. These results suggest that the extent of pathogen growth is affected not only by the concentration but also by the composition of AOC. Through this bioassay, PGP can be included as a parameter in water treatment system design, control, and operation. Additionally, a multilevel concept that integrates the results from the bioassay into the bigger framework of pathogen growth in water is discussed. The proposed approach provides a first step for including pathogen growth into microbial risk assessment.Pathogenic bacteria can survive and also grow in lownutrient aquatic environments, such as surface waters or man-made water treatment systems (2,17,30). Studies on pathogen survival and/or die-off (including disinfection) in water are common, but little is known about the fundamental factors governing their growth in the environment (34,35). Understanding the growth of pathogenic bacteria in aquatic ecosystems is essential for a holistic approach to microbial risk assessment as well as for improving drinking water treatment design and operation.

SummaryColonial medical reports claimed that tuberculosis (TB) was largely unknown in Africa prior to European contact, providing a “virgin soil” for spread of TB in highly susceptible populations previously unexposed to the disease [1, 2]. This is in direct contrast to recent phylogenetic models which support an African origin for TB [3, 4, 5, 6]. To address this apparent contradiction, we performed a broad genomic sampling of Mycobacterium tuberculosis in Ethiopia. All members of the M. tuberculosis complex (MTBC) arose from clonal expansion of a single common ancestor [7] with a proposed origin in East Africa [3, 4, 8]. Consistent with this proposal, MTBC lineage 7 is almost exclusively found in that region [9, 10, 11]. Although a detailed medical history of Ethiopia supports the view that TB was rare until the 20th century [12], over the last century Ethiopia has become a high-burden TB country [13]. Our results provide further support for an African origin for TB, with some genotypes already present on the continent well before European contact. Phylogenetic analyses reveal a pattern of serial introductions of multiple genotypes into Ethiopia in association with human migration and trade. In place of a “virgin soil” fostering the spread of TB in a previously naive population, we propose that increased TB mortality in Africa was driven by the introduction of European strains of M. tuberculosis alongside expansion of selected indigenous strains having biological characteristics that carry a fitness benefit in the urbanized settings of post-colonial Africa.

Strain-specific SNP genotyping allowed rapid and inexpensive identification of M. tuberculosis outbreak isolates in a population-based strain collection. Subsequent targeted WGS provided detailed insights into transmission dynamics. This combined approach could be applied to track bacterial pathogens in real time and at high resolution.

ObjectiveThe aim of this study was to use spoligotyping and large sequence polymorphism (LSP) to study the population structure of M. tuberculosis complex (MTBC) isolates.MethodsMTBC isolates were identified using standard biochemical procedures, IS6110 PCR, and large sequence polymorphisms. Isolates were further typed using spoligotyping, and the phenotypic drug susceptibility patterns were determined by the proportion method.ResultOne hundred and sixty-two isolates were characterised by LSP typing. Of these, 130 (80.25%) were identified as Mycobacterium tuberculosis sensu stricto (MTBss), with the Cameroon sub-lineage being dominant (N = 59/130, 45.38%). Thirty-two (19.75%) isolates were classified as Mycobacterium africanum type 1, and of these 26 (81.25%) were identified as West-Africa I, and 6 (18.75%) as West-Africa II. Spoligotyping sub-lineages identified among the MTBss included Haarlem (N = 15, 11.53%), Ghana (N = 22, 16.92%), Beijing (4, 3.08%), EAI (4, 3.08%), Uganda I (4, 3.08%), LAM (2, 1.54%), X (N = 1, 0.77%) and S (2, 1.54%). Nine isolates had SIT numbers with no identified sub-lineages while 17 had no SIT numbers. MTBss isolates were more likely to be resistant to streptomycin (p<0.008) and to any drug resistance (p<0.03) when compared to M. africanum.ConclusionThis study demonstrated that overall 36.4% of TB in South-Western Ghana is caused by the Cameroon sub-lineage of MTBC and 20% by M. africanum type 1, including both the West-Africa 1 and West-Africa 2 lineages. The diversity of MTBC in Ghana should be considered when evaluating new TB vaccines.