Benchmarking the empirical accuracy of short-read sequencing across the M. tuberculosis genome

Exploring gene content with pangene graphs

Motivation

The gene content regulates the biology of an organism. It varies between species and between individuals of the same species. Although tools have been developed to identify gene content changes in bacterial genomes, none is applicable to collections of large eukaryotic genomes such as the human pangenome.

Results

We developed pangene, a computational tool to identify gene orientation, gene order and gene copy-number changes in a collection of genomes. Pangene aligns a set of input protein sequences to the genomes, resolves redundancies between protein sequences and constructs a gene graph with each genome represented as a walk in the graph. It additionally finds subgraphs, which we call bibubbles, that capture gene content changes. Applied to the human pangenome, pangene identifies known gene-level variations and reveals complex haplotypes that are not well studied before. Pangene also works with high-quality bacterial pangenome and reports similar numbers of core and accessory genes in comparison to existing tools.

Availability and implementation

Source code at https://github.com/lh3/pangene; pre-built pangene graphs can be downloaded from https://zenodo.org/records/8118576 and visualized at https://pangene.bioinweb.org.

Analysis of the limited M. tuberculosis accessory genome reveals potential pitfalls of pan-genome analysis approaches

Pan-genome analysis is a fundamental tool for studying bacterial genome evolution; however, the variety of methods used to define and measure the pan-genome poses challenges to the interpretation and reliability of results. To quantify sources of bias and error related to common pan-genome analysis approaches, we evaluated different approaches applied to curated collection of 151 Mycobacterium tuberculosis ( Mtb ) isolates. Mtb is characterized by its clonal evolution, absence of horizontal gene transfer, and limited accessory genome, making it an ideal test case for this study. Using a state-of-the-art graph-genome approach, we found that a majority of the structural variation observed in Mtb originates from rearrangement, deletion, and duplication of redundant nucleotide sequences. In contrast, we found that pan-genome analyses that focus on comparison of coding sequences (at the amino acid level) can yield surprisingly variable results, driven by differences in assembly quality and the softwares used. Upon closer inspection, we found that coding sequence annotation discrepancies were a major contributor to inflated Mtb accessory genome estimates. To address this, we developed panqc, a software that detects annotation discrepancies and collapses nucleotide redundancy in pan-genome estimates. When applied to Mtb and E. coli pan-genomes, panqc exposed distinct biases influenced by the genomic diversity of the population studied. Our findings underscore the need for careful methodological selection and quality control to accurately map the evolutionary dynamics of a bacterial species.

Mycobacterial DnaQ is an Alternative Proofreader Ensuring DNA Replication Fidelity

Remove of mis-incorporated nucleotides ensures replicative fidelity. Although the ε-exonuclease DnaQ is a well-established proofreader in the model organism Escherichia coli, proofreading in mycobacteria relies on the polymerase and histidinol phosphatase (PHP) domain of replicative polymerase despite the presence of an alternative DnaQ homolog. Here, we show that depletion of DnaQ in Mycolicibacterium smegmatis results in increased mutation rate, leading to AT-biased mutagenesis and elevated insertions/deletions in homopolymer tract. We demonstrated that mycobacterial DnaQ binds to the b-clamp and functions synergistically with the PHP domain to correct replication errors. Further, we found that the mycobacterial DnaQ sustains replicative fidelity upon chromosome topological stress. Intriguingly, we showed that a naturally evolved DnaQ variant prevalent in clinical Mycobacterium tuberculosis isolates enables hypermutability and is associated with extensive drug resistance. These results collectively establish that the alternative DnaQ functions in proofreading, and thus reveal that mycobacteria deploy two proofreaders to maintain replicative fidelity.

Genomic epidemiology analysis of drug-resistant Mycobacterium tuberculosis distributed in Mexico

Genomics has significantly revolutionized pathogen surveillance, particularly in epidemiological studies, the detection of drug-resistant strains, and disease control. Despite its potential, the representation of Latin American countries in the genomic catalogues of Mycobacterium tuberculosis (Mtb), the bacteria responsible for Tuberculosis (TB), remains limited. In this study, we present a whole genome sequencing (WGS)-based analysis of 85 Mtb clinical strains from 17 Mexican states, providing insights into local adaptations and drug resistance signatures in the region. Our results reveal that the Euro-American lineage (L4) accounts for 94% of our dataset, showing 4.1.2.1 (Haarlem, n = 32), and 4.1.1.3 (X-type, n = 34) sublineages as the most prevalent. We report the presence of the 4.1.1.3 sublineage, which is endemic to Mexico, in six additional locations beyond previous reports. Phenotypic drug resistance tests showed that 34 out of 85 Mtb samples were resistant, exhibiting a variety of resistance profiles to the first-line antibiotics tested. We observed high levels of discrepancy between phenotype and genotype associated with drug resistance in our dataset, including pyrazinamide-monoresistant Mtb strains lacking canonical variants of drug resistance. Expanding the Latin American Mtb genome databases will enhance our understanding of TB epidemiology and potentially provide new avenues for controlling the disease in the region.

Functional genetic variation in pe/ppe genes contributes to diversity in Mycobacterium tuberculosis lineages and potential interactions with the human host

Introduction

Around 10% of the coding potential of Mycobacterium tuberculosisis constituted by two poorly understood gene families, the pe and ppe loci, thought to be involved in host-pathogen interactions. Their repetitive nature and high GC content have hindered sequence analysis, leading to exclusion from whole-genome studies. Understanding the genetic diversity of pe/ppe families is essential to facilitate their potential translation into tools for tuberculosis prevention and treatment.

Methods

To investigate the genetic diversity of the 169 pe/ppe genes, we performed a sequence analysis across 73 long-read assemblies representing seven different lineages of M. tuberculosis and M. bovis BCG. Individual pe/ppe gene alignments were extracted and diversity and conservation across the different lineages studied.

Results

The pe/ppe genes were classified into three groups based on the level of protein sequence conservation relative to H37Rv, finding that >50% were conserved, with indels in pe_pgrs and ppe_mptr sub-families being major drivers of structural variation. Gene rearrangements, such as duplications and gene fusions, were observed between pe and pe_pgrs genes. Inter-lineage diversity revealed lineage-specific SNPs and indels.

Discussion

The high level of pe/ppe genes conservation, together with the lineage-specific findings, suggest their phylogenetic informativeness. However, structural variants and gene rearrangements differing from the reference were also identified, with potential implications for pathogenicity. Overall, improving our knowledge of these complex gene families may have insights into pathogenicity and inform the development of much-needed tools for tuberculosis control.

Mutation rates and adaptive variation among the clinically dominant clusters of Mycobacterium abscessus

Mycobacterium abscessus (Mab) is a multidrug-resistant pathogen increasingly responsible for severe pulmonary infections. Analysis of whole-genome sequences (WGS) of Mab demonstrates dense genetic clustering of clinical isolates collected from disparate geographic locations. This has been interpreted as supporting patient-to-patient transmission, but epidemiological studies have contradicted this interpretation. Here, we present evidence for a slowing of the Mab molecular clock rate coincident with the emergence of phylogenetic clusters. We performed phylogenetic inference using publicly available WGS from 483 Mab patient isolates. We implement a subsampling approach in combination with coalescent analysis to estimate the molecular clock rate along the long internal branches of the tree, indicating a faster long-term molecular clock rate compared to branches within phylogenetic clusters. We used ancestry simulation to predict the effects of clock rate variation on phylogenetic clustering and found that the degree of clustering in the observed phylogeny is more easily explained by a clock rate slowdown than by transmission. We also find that phylogenetic clusters are enriched in mutations affecting DNA repair machinery and report that clustered isolates have lower spontaneous mutation rates in vitro. We propose that Mab adaptation to the host environment through variation in DNA repair genes affects the organism's mutation rate and that this manifests as phylogenetic clustering. These results challenge the model that phylogenetic clustering in Mab is explained by person-to-person transmission and inform our understanding of transmission inference in emerging, facultative pathogens.

Advantages of long- and short-reads sequencing for the hybrid investigation of the Mycobacterium tuberculosis genome

Introduction

In the fight to limit the global spread of antibiotic resistance, computational challenges associated with sequencing technology can impact the accuracy of downstream analysis, including drug resistance identification, transmission, and genome resolution. About 10% of Mycobacterium tuberculosis (MTB) genome is constituted by the PE/PPE family, a GC-rich repetitive genome region. Although sequencing using short read technology is widely used, it is well recognized its limit in the PE/PPE regions due to the unambiguously mapping process onto the reference genome. The aim of this study was to compare the performances of short-reads (SRS), long-reads (LRS) and hybrid-reads (HYBR) based analysis over different common investigative tasks: genome coverage estimation, variant calling and cluster analysis, drug resistance detection and de novo assembly.

Methods

For the study 13 model MTB clinical isolates were sequenced with both SRS and LRS. HYBR were produced correcting the long reads with the short reads. The fastq from the three approaches were then processed using a customized version of MTBseq for genome coverage estimation and variant calling and using two different assemblers for de novo assembly evaluation.

Results

Estimation of genome coverage performances showed lower 8X breadth coverage for SRS respect to LRS and HYBR: considering the PE/PPE genes, SRS showed low results for the PE_PGRS family, while obtained acceptable coverage in PE and PPE genes; LRS and HYBR reached optimal coverages in PE/PPE genes. For variant calling HYBR showed the highest resolution, detecting the highest percentage of uniquely identified mutations compared to LRS and SRS. All three approaches agreed on the identification of two major clusters, with HYBR identifying an higher number of SNPs between the two clusters. Comparing the quality of the assemblies, HYBR and LRS obtained better results than SRS.

Discussion

In conclusion, depending on the aim of the investigation, both SRS and LRS present complementary advantages and limitations implying that for a full resolution of MTB genomes, where all the mentioned analyses and both technologies are needed, the use of the HYBR approach represents a valid option and a well-rounded strategy.

Tuberculosis treatment failure associated with evolution of antibiotic resilience

The widespread use of antibiotics has placed bacterial pathogens under intense pressure to evolve new survival mechanisms. Genomic analysis of 51,229 Mycobacterium tuberculosis (Mtb)clinical isolates has identified an essential transcriptional regulator, Rv1830, herein called resR for resilience regulator, as a frequent target of positive (adaptive) selection. resR mutants do not show canonical drug resistance or drug tolerance but instead shorten the post-antibiotic effect, meaning that they enable Mtb to resume growth after drug exposure substantially faster than wild-type strains. We refer to this phenotype as antibiotic resilience. ResR acts in a regulatory cascade with other transcription factors controlling cell growth and division, which are also under positive selection in clinical isolates of Mtb. Mutations of these genes are associated with treatment failure and the acquisition of canonical drug resistance.

Portable sequencing of Mycobacterium tuberculosis for clinical and epidemiological applications

With >1 million associated deaths in 2020, human tuberculosis (TB) caused by the bacteria Mycobacterium tuberculosis remains one of the deadliest infectious diseases. A plethora of genomic tools and bioinformatics pipelines have become available in recent years to assist the whole genome sequencing of M. tuberculosis. The Oxford Nanopore Technologies (ONT) portable sequencer is a promising platform for cost-effective application in clinics, including personalizing treatment through detection of drug resistance-associated mutations, or in the field, to assist epidemiological and transmission investigations. In this study, we performed a comparison of 10 clinical isolates with DNA sequenced on both long-read ONT and (gold standard) short-read Illumina HiSeq platforms. Our analysis demonstrates the robustness of the ONT variant calling for single nucleotide polymorphisms, despite the high error rate. Moreover, because of improved coverage in repetitive regions where short sequencing reads fail to align accurately, ONT data analysis can incorporate additional regions of the genome usually excluded (e.g. pe/ppe genes). The resulting extra resolution can improve the characterization of transmission clusters and dynamics based on inferring closely related isolates. High concordance in variants in loci associated with drug resistance supports its use for the rapid detection of resistant mutations. Overall, ONT sequencing is a promising tool for TB genomic investigations, particularly to inform clinical and surveillance decision-making to reduce the disease burden.

A convolutional neural network highlights mutations relevant to antimicrobial resistance in Mycobacterium tuberculosis

Long diagnostic wait times hinder international efforts to address antibiotic resistance in M. tuberculosis. Pathogen whole genome sequencing, coupled with statistical and machine learning models, offers a promising solution. However, generalizability and clinical adoption have been limited by a lack of interpretability, especially in deep learning methods. Here, we present two deep convolutional neural networks that predict antibiotic resistance phenotypes of M. tuberculosis isolates: a multi-drug CNN (MD-CNN), that predicts resistance to 13 antibiotics based on 18 genomic loci, with AUCs 82.6-99.5% and higher sensitivity than state-of-the-art methods; and a set of 13 single-drug CNNs (SD-CNN) with AUCs 80.1-97.1% and higher specificity than the previous state-of-the-art. Using saliency methods to evaluate the contribution of input sequence features to the SD-CNN predictions, we identify 18 sites in the genome not previously associated with resistance. The CNN models permit functional variant discovery, biologically meaningful interpretation, and clinical applicability.