Recombination Signal in Mycobacterium tuberculosis Stems from Reference-guided Assemblies and Alignment Artefacts

Evolution and emergence of Mycobacterium tuberculosis

Tuberculosis (TB) remains one of the deadliest infectious diseases in human history, prevailing even in the 21st century. The causative agents of TB are represented by a group of closely related bacteria belonging to the Mycobacterium tuberculosis complex (MTBC), which can be subdivided into several lineages of human- and animal-adapted strains, thought to have shared a last common ancestor emerged by clonal expansion from a pool of recombinogenic Mycobacterium canettii-like tubercle bacilli. A better understanding of how MTBC populations evolved from less virulent mycobacteria may allow for discovering improved TB control strategies and future epidemiologic trends. In this review, we highlight new insights into the evolution of mycobacteria at the genus level, describing different milestones in the evolution of mycobacteria, with a focus on the genomic events that have likely enabled the emergence and the dominance of the MTBC. We also review the recent literature describing the various MTBC lineages and highlight their particularities and differences with a focus on host preferences and geographic distribution. Finally, we discuss on putative mechanisms driving the evolution of tubercle bacilli and mycobacteria in general, by taking the mycobacteria-specific distributive conjugal transfer as an example.

Drug resistance prediction for Mycobacterium tuberculosis with reference graphs

Tuberculosis is a global pandemic disease with a rising burden of antimicrobial resistance. As a result, the World Health Organization (WHO) has a goal of enabling universal access to drug susceptibility testing (DST). Given the slowness of and infrastructure requirements for phenotypic DST, whole-genome sequencing, followed by genotype-based prediction of DST, now provides a route to achieving this. Since a central component of genotypic DST is to detect the presence of any known resistance-causing mutations, a natural approach is to use a reference graph that allows encoding of known variation. We have developed DrPRG (Drug resistance Prediction with Reference Graphs) using the bacterial reference graph method Pandora. First, we outline the construction of a Mycobacterium tuberculosis drug resistance reference graph. The graph is built from a global dataset of isolates with varying drug susceptibility profiles, thus capturing common and rare resistance- and susceptible-associated haplotypes. We benchmark DrPRG against the existing graph-based tool Mykrobe and the haplotype-based approach of TBProfiler using 44 709 and 138 publicly available Illumina and Nanopore samples with associated phenotypes. We find that DrPRG has significantly improved sensitivity and specificity for some drugs compared to these tools, with no significant decreases. It uses significantly less computational memory than both tools, and provides significantly faster runtimes, except when runtime is compared to Mykrobe with Nanopore data. We discover and discuss novel insights into resistance-conferring variation for M. tuberculosis - including deletion of genes katG and pncA - and suggest mutations that may warrant reclassification as associated with resistance.

Evolution of Tuberculosis Pathogenesis

Mycobacterium tuberculosis is a globally distributed, lethal pathogen of humans. The virulence armamentarium of M. tuberculosis appears to have been developed on a scaffold of antiphagocytic defenses found among diverse, mostly free-living species of Mycobacterium. Pathoadaptation was further aided by the modularity, flexibility, and interactivity characterizing mycobacterial effectors and their regulators. During emergence of M. tuberculosis, novel genetic material was acquired, created, and integrated with existing tools. The major mutational mechanisms underlying these adaptations are discussed in this review, with examples. During its evolution, M. tuberculosis lost the ability and/or opportunity to engage in lateral gene transfer, but despite this it has retained the adaptability that characterizes mycobacteria. M. tuberculosis exemplifies the evolutionary genomic mechanisms underlying adoption of the pathogenic niche, and studies of its evolution have uncovered a rich array of discoveries about how new pathogens are made. Expected final online publication date for the Annual Review of Microbiology, Volume 76 is September 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Current Methods for Recombination Detection in Bacteria

The role of genetic exchanges, i.e., homologous recombination (HR) and horizontal gene transfer (HGT), in bacteria cannot be overestimated for it is a pivotal mechanism leading to their evolution and adaptation, thus, tracking the signs of recombination and HGT events is importance both for fundamental and applied science. To date, dozens of bioinformatics tools for revealing recombination signals are available, however, their pros and cons as well as the spectra of solvable tasks have not yet been systematically reviewed. Moreover, there are two major groups of software. One aims to infer evidence of HR, while the other only deals with horizontal gene transfer (HGT). However, despite seemingly different goals, all the methods use similar algorithmic approaches, and the processes are interconnected in terms of genomic evolution influencing each other. In this review, we propose a classification of novel instruments for both HR and HGT detection based on the genomic consequences of recombination. In this context, we summarize available methodologies paying particular attention to the type of traceable events for which a certain program has been designed.

A critical evaluation of Mycobacterium bovis pangenomics, with reference to its utility in outbreak investigation

The increased accessibility of next generation sequencing has allowed enough genomes from a given bacterial species to be sequenced to describe the distribution of genes in the pangenome, without limiting analyses to genes present in reference strains. Although some taxa have thousands of whole genome sequences available on public databases, most genomes were sequenced with short read technology, resulting in incomplete assemblies. Studying pangenomes could lead to important insights into adaptation, pathogenicity, or molecular epidemiology, however given the known information loss inherent in analyzing contig-level assemblies, these inferences may be biased or inaccurate. In this study we describe the pangenome of a clonally evolving pathogen, Mycobacterium bovis , and examine the utility of gene content variation in M. bovis outbreak investigation. We constructed the M. bovis pangenome using 1463 de novo assembled genomes. We tested the assumption of strict clonal evolution by studying evidence of recombination in core genes and analyzing the distribution of accessory genes among core monophyletic groups. To determine if gene content variation could be utilized in outbreak investigation, we carefully examined accessory genes detected in a well described M. bovis outbreak in Minnesota. We found significant errors in accessory gene classification. After accounting for these errors, we show that M. bovis has a much smaller accessory genome than previously described and provide evidence supporting ongoing clonal evolution and a closed pangenome, with little gene content variation generated over outbreaks. We also identified frameshift mutations in multiple genes, including a mutation in glpK, which has recently been associated with antibiotic tolerance in Mycobacterium tuberculosis . A pangenomic approach enables a more comprehensive analysis of genome dynamics than is possible with reference-based approaches; however, without critical evaluation of accessory gene content, inferences of transmission patterns employing these loci could be misguided.

The impact of frequently neglected model violations on bacterial recombination rate estimation: a case study in Mycobacterium canettii and Mycobacterium tuberculosis

Mycobacterium canettii is a causative agent of tuberculosis in humans, along with the members of the Mycobacterium tuberculosis complex. Frequently used as an outgroup to the M. tuberculosis complex in phylogenetic analyses, M. canettii is thought to offer the best proxy for the progenitor species that gave rise to the complex. Here, we leverage whole-genome sequencing data and biologically relevant population genomic models to compare the evolutionary dynamics driving variation in the recombining M. canettii with that in the nonrecombining M. tuberculosis complex, and discuss differences in observed genomic diversity in the light of expected levels of Hill-Robertson interference. In doing so, we highlight the methodological challenges of estimating recombination rates through traditional population genetic approaches using sequences called from populations of microorganisms and evaluate the likely mis-inference that arises owing to a neglect of common model violations including purifying selection, background selection, progeny skew, and population size change. In addition, we compare performance when full within-host polymorphism data are utilized, versus the more common approach of basing analyses on within-host consensus sequences.

Mutation bias shapes the spectrum of adaptive substitutions

How do mutational biases influence the process of adaptation? A common assumption is that selection alone determines the course of adaptation from abundant preexisting variation. Yet, theoretical work shows broad conditions under which the mutation rate to a given type of variant strongly influences its probability of contributing to adaptation. Here we introduce a statistical approach to analyzing how mutation shapes protein sequence adaptation. Using large datasets from three different species, we show that the mutation spectrum has a proportional influence on the types of changes fixed in adaptation. We also show via computer simulations that a variety of factors can influence how closely the spectrum of adaptive substitutions reflects the spectrum of variants introduced by mutation.

Evolutionary adaptation often occurs by the fixation of beneficial mutations. This mode of adaptation can be characterized quantitatively by a spectrum of adaptive substitutions, i.e., a distribution for types of changes fixed in adaptation. Recent work establishes that the changes involved in adaptation reflect common types of mutations, raising the question of how strongly the mutation spectrum shapes the spectrum of adaptive substitutions. We address this question with a codon-based model for the spectrum of adaptive amino acid substitutions, applied to three large datasets covering thousands of amino acid changes identified in natural and experimental adaptation in Saccharomyces cerevisiae, Escherichia coli, and Mycobacterium tuberculosis. Using species-specific mutation spectra based on prior knowledge, we find that the mutation spectrum has a proportional influence on the spectrum of adaptive substitutions in all three species. Indeed, we find that by inferring the mutation rates that best explain the spectrum of adaptive substitutions, we can accurately recover the species-specific mutation spectra. However, we also find that the predictive power of the model differs substantially between the three species. To better understand these differences, we use population simulations to explore the factors that influence how closely the spectrum of adaptive substitutions mirrors the mutation spectrum. The results show that the influence of the mutation spectrum decreases with increasing mutational supply (Nμ) and that predictive power is strongly affected by the number and diversity of beneficial mutations.

Performance and Agreement Between WGS Variant Calling Pipelines Used for Bovine Tuberculosis Control: Toward International Standardization

Whole genome sequencing (WGS) and allied variant calling pipelines are a valuable tool for the control and eradication of infectious diseases, since they allow the assessment of the genetic relatedness of strains of animal pathogens. In the context of the control of tuberculosis (TB) in livestock, mainly caused by Mycobacterium bovis, these tools offer a high-resolution alternative to traditional molecular methods in the study of herd breakdown events. However, despite the increased use and efforts in the standardization of WGS methods in human tuberculosis around the world, the application of these WGS-enabled approaches to control TB in livestock is still in early development. Our study pursued an initial evaluation of the performance and agreement of four publicly available pipelines for the analysis of M. bovis WGS data (vSNP, SNiPgenie, BovTB, and MTBseq) on a set of simulated Illumina reads generated from a real-world setting with high TB prevalence in cattle and wildlife in the Republic of Ireland. The overall performance of the evaluated pipelines was high, with recall and precision rates above 99% once repeat-rich and problematic regions were removed from the analyses. In addition, when the same filters were applied, distances between inferred phylogenetic trees were similar and pairwise comparison revealed that most of the differences were due to the positioning of polytomies. Hence, under the studied conditions, all pipelines offer similar performance for variant calling to underpin real-world studies of M. bovis transmission dynamics.

A new nomenclature for the livestock-associated Mycobacterium tuberculosis complex based on phylogenomics

Background:  The bacteria that compose the Mycobacterium tuberculosis complex (MTBC) cause tuberculosis (TB) in humans and in different animals, including livestock. Much progress has been made in understanding the population structure of the human-adapted members of the MTBC by combining phylogenetics with genomics. Accompanying the discovery of new genetic diversity, a body of operational nomenclature has evolved to assist comparative and molecular epidemiological studies of human TB. By contrast, for the livestock-associated MTBC members, Mycobacterium bovis, M. caprae and M. orygis, there has been a lack of comprehensive nomenclature to accommodate new genetic diversity uncovered by emerging phylogenomic studies. We propose to fill this gap by putting forward a new nomenclature covering the main phylogenetic groups within M. bovis, M. caprae and M. orygis. Methods:  We gathered a total of 8,736 whole-genome sequences (WGS) from public sources and 39 newly sequenced strains, and selected a subset of 829 WGS, representative of the worldwide diversity of M. bovis, M. caprae and M. orygis. We used phylogenetics and genetic diversity patterns inferred from WGS to define groups. Results:  We propose to divide M. bovis, M. caprae and M. orygis in three main phylogenetic lineages, which we named La1, La2 and La3, respectively. Within La1, we identified several monophyletic groups, which we propose to classify into eight sublineages (La1.1-La1.8). These sublineages differed in geographic distribution, with some being geographically restricted and others globally widespread, suggesting different expansion abilities. To ease molecular characterization of these MTBC groups by the community, we provide phylogenetically informed, single nucleotide polymorphisms that can be used as barcodes for genotyping. These markers were implemented in KvarQ and TB-Profiler, which are platform-independent, open-source tools. Conclusions:  Our results contribute to an improved classification of the genetic diversity within the livestock-associated MTBC, which will benefit future molecular epidemiological and evolutionary studies.

Genome-wide estimation of recombination, mutation and positive selection enlightens diversification drivers of Mycobacterium bovis

Genome sequencing has reinvigorated the infectious disease research field, shedding light on disease epidemiology, pathogenesis, host-pathogen interactions and also evolutionary processes exerted upon pathogens. Mycobacterium tuberculosis complex (MTBC), enclosing M. bovis as one of its animal-adapted members causing tuberculosis (TB) in terrestrial mammals, is a paradigmatic model of bacterial evolution. As other MTBC members, M. bovis is postulated as a strictly clonal, slowly evolving pathogen, with apparently no signs of recombination or horizontal gene transfer. In this work, we applied comparative genomics to a whole genome sequence (WGS) dataset composed by 70 M. bovis from different lineages (European and African) to gain insights into the evolutionary forces that shape genetic diversification in M. bovis. Three distinct approaches were used to estimate signs of recombination. Globally, a small number of recombinant events was identified and confirmed by two independent methods with solid support. Still, recombination reveals a weaker effect on M. bovis diversity compared with mutation (overall r/m = 0.037). The differential r/m average values obtained across the clonal complexes of M. bovis in our dataset are consistent with the general notion that the extent of recombination may vary widely among lineages assigned to the same taxonomical species. Based on this work, recombination in M. bovis cannot be excluded and should thus be a topic of further effort in future comparative genomics studies for which WGS of large datasets from different epidemiological scenarios across the world is crucial. A smaller M. bovis dataset (n = 42) from a multi-host TB endemic scenario was then subjected to additional analyses, with the identification of more than 1,800 sites wherein at least one strain showed a single nucleotide polymorphism (SNP). The majority (87.1%) was located in coding regions, with the global ratio of non-synonymous upon synonymous alterations (dN/dS) exceeding 1.5, suggesting that positive selection is an important evolutionary force exerted upon M. bovis. A higher percentage of SNPs was detected in genes enriched into "lipid metabolism", "cell wall and cell processes" and "intermediary metabolism and respiration" functional categories, revealing their underlying importance in M. bovis biology and evolution. A closer look on genes prone to horizontal gene transfer in the MTBC ancestor and included in the 3R (DNA repair, replication and recombination) system revealed a global average negative value for Taijima's D neutrality test, suggesting that past selective sweeps and population expansion after a recent bottleneck remain as major evolutionary drivers of the obligatory pathogen M. bovis in its struggle with the host.

ESX-1-Independent Horizontal Gene Transfer by Mycobacterium tuberculosis Complex Strains

Current models of horizontal gene transfer (HGT) in mycobacteria are based on “distributive conjugal transfer” (DCT), an HGT type described in the fast-growing, saprophytic model organism Mycobacterium smegmatis, which creates genome mosaicism in resulting strains and depends on an ESX-1 type VII secretion system. In contrast, only few data on interstrain DNA transfer are available for tuberculosis-causing mycobacteria, for which chromosomal DNA transfer between two Mycobacterium canettii strains was reported, a process which, however, was not observed for Mycobacterium tuberculosis strains. Here, we have studied a wide range of human- and animal-adapted members of the Mycobacterium tuberculosis complex (MTBC) using an optimized filter-based mating assay together with three selected strains of M. canettii that acted as DNA recipients. Unlike in previous approaches, we obtained a high yield of thousands of recombinants containing transferred chromosomal DNA fragments from various MTBC donor strains, as confirmed by whole-genome sequence analysis of 38 randomly selected clones. While the genome organizations of the obtained recombinants showed mosaicisms of donor DNA fragments randomly integrated into a recipient genome backbone, reminiscent of those described as being the result of ESX-1-mediated DCT in M. smegmatis, we observed similar transfer efficiencies when ESX-1-deficient donor and/or recipient mutants were used, arguing that in tubercle bacilli, HGT is an ESX-1-independent process. These findings provide new insights into the genetic events driving the pathoevolution of M. tuberculosis and radically change our perception of HGT in mycobacteria, particularly for those species that show recombinogenic population structures despite the natural absence of ESX-1 secretion systems.

GenomegaMap: Within-Species Genome-Wide dN/dS Estimation from over 10,000 Genomes

The dN/dS ratio provides evidence of adaptation or functional constraint in protein-coding genes by quantifying the relative excess or deficit of amino acid-replacing versus silent nucleotide variation. Inexpensive sequencing promises a better understanding of parameters, such as dN/dS, but analyzing very large data sets poses a major statistical challenge. Here, I introduce genomegaMap for estimating within-species genome-wide variation in dN/dS, and I apply it to 3,979 genes across 10,209 tuberculosis genomes to characterize the selection pressures shaping this global pathogen. GenomegaMap is a phylogeny-free method that addresses two major problems with existing approaches: 1) It is fast no matter how large the sample size and 2) it is robust to recombination, which causes phylogenetic methods to report artefactual signals of adaptation. GenomegaMap uses population genetics theory to approximate the distribution of allele frequencies under general, parent-dependent mutation models. Coalescent simulations show that substitution parameters are well estimated even when genomegaMap’s simplifying assumption of independence among sites is violated. I demonstrate the ability of genomegaMap to detect genuine signatures of selection at antimicrobial resistance-conferring substitutions in Mycobacterium tuberculosis and describe a novel signature of selection in the cold-shock DEAD-box protein A gene deaD/csdA. The genomegaMap approach helps accelerate the exploitation of big data for gaining new insights into evolution within species.

Whole genome phylogenies reflect the distributions of recombination rates for many bacterial species

Although recombination is accepted to be common in bacteria, for many species robust phylogenies with well-resolved branches can be reconstructed from whole genome alignments of strains, and these are generally interpreted to reflect clonal relationships. Using new methods based on the statistics of single-nucleotide polymorphism (SNP) splits, we show that this interpretation is incorrect. For many species, each locus has recombined many times along its line of descent, and instead of many loci supporting a common phylogeny, the phylogeny changes many thousands of times along the genome alignment. Analysis of the patterns of allele sharing among strains shows that bacterial populations cannot be approximated as either clonal or freely recombining but are structured such that recombination rates between lineages vary over several orders of magnitude, with a unique pattern of rates for each lineage. Thus, rather than reflecting clonal ancestry, whole genome phylogenies reflect distributions of recombination rates.

Insertion and deletion evolution reflects antibiotics selection pressure in a Mycobacterium tuberculosis outbreak

In genome evolution, genetic variants are the source of diversity, which natural selection acts upon. Treatment of human tuberculosis (TB) induces a strong selection pressure for the emergence of antibiotic resistance-conferring variants in the infecting Mycobacterium tuberculosis (MTB) strains. MTB evolution in response to treatment has been intensively studied and mainly attributed to point substitutions. However, the frequency and contribution of insertions and deletions (indels) to MTB genome evolution remains poorly understood. Here, we analyzed a multi-drug resistant MTB outbreak for the presence of high-quality indels and substitutions. We find that indels are significantly enriched in genes conferring antibiotic resistance. Furthermore, we show that indels are inherited during the outbreak and follow a molecular clock with an evolutionary rate of 5.37e-9 indels/site/year, which is 23 times lower than the substitution rate. Inherited indels may co-occur with substitutions in genes along related biological pathways; examples are iron storage and resistance to second-line antibiotics. This suggests that epistatic interactions between indels and substitutions affect antibiotic resistance and compensatory evolution in MTB.

Producing polished prokaryotic pangenomes with the Panaroo pipeline

Population-level comparisons of prokaryotic genomes must take into account the substantial differences in gene content resulting from horizontal gene transfer, gene duplication and gene loss. However, the automated annotation of prokaryotic genomes is imperfect, and errors due to fragmented assemblies, contamination, diverse gene families and mis-assemblies accumulate over the population, leading to profound consequences when analysing the set of all genes found in a species. Here, we introduce Panaroo, a graph-based pangenome clustering tool that is able to account for many of the sources of error introduced during the annotation of prokaryotic genome assemblies. Panaroo is available at https://github.com/gtonkinhill/panaroo .

ESX/Type VII Secretion Systems-An Important Way Out for Mycobacterial Proteins

The causative agent of human tuberculosis, Mycobacterium tuberculosis, has a complex lipid-rich diderm envelope, which acts as a major barrier protecting the bacterium against the hostile environment inside the host cells. For the transfer of diverse molecules across this complex cell envelope, M. tuberculosis has a series of general and specialized protein secretion systems, characterized by the SecA general secretion pathway, the twin-arginine translocation pathway, and five specific ESX type VII secretion systems. In this review, we focus on the latter systems, known as ESX-1 to ESX-5, which were first discovered almost 20 years ago during the in silico analysis of the genome sequence of M. tuberculosis H37Rv. Since then, these systems have been the subject of highly dynamic research due to their involvement in several key biological processes and host-pathogen interactions of the tubercle bacilli.