Biology subjects

Borrell, S.

Publications and source records attributed to Borrell, S..

At least 19 recordsLinked to original sources

bioRxiv2026

Evolutionary dynamics of the insertion sequence IS6110 in the Mycobacterium tuberculosis complex

Insertion sequences (IS) are the most common type of transposable element in prokaryotes and shape the structure of genomes through transposition and by providing a substrate for recombination. Despite the mutational impact of IS, the evolutionary dynamics of most elements in host species remain unknown. Here we study the dynamics of IS6110 in 10,000 strains of the Mycobacterium tuberculosis complex (MTBC). We developed a tool that allows the detection and comparison of IS insertions from short reads without using a reference genome. Using ancestral state reconstruction (ASR) on presence-absence patterns of IS6110, we describe the distribution of copy numbers (CNs) in the MTBC, infer birth rates of the element, and identify genomic regions with large numbers of parallel IS6110 insertions. Copy numbers in the MTBC range from 1 in some clades to more than 30 in strains of La3 (M. orygis). IS6110 birth rates scale approximately linearly with copy number and are elevated on terminal branches, consistent with the delayed action of purifying selection. A key characteristic of IS6110 is its occurrence in hotspots: the 5% most frequently targeted regions account for half of all independent insertion events. The motif 5'-TCTCAAAW-3' is enriched around target sites and in hotspots, suggesting that the accumulation of insertions in these regions results through a combination of non-random insertion and purifying selection in other regions. To conclude the study, we propose a niche constraints model according to which the distribution of IS6110 in the MTBC is governed by the rarity of regions that have both suitable DNA properties and little functional value for the host.

genomics↗

bioRxiv2024

Antibiotic lethality dictates mycobacterial infection outcomes

Antibiotic development and treatment focus on bacterial growth inhibition, often with limited success. Here, we introduce Antimicrobial Single-Cell Testing (ASCT), an advanced imaging strategy to assess bacterial killing in real-time. By tracking 140 million bacteria and generating over 20,000 in vitro time-kill curves, we can predict Mycobacterium tuberculosis treatment outcomes in mice and humans and link strain-specific survival (drug tolerance) in Mycobacterium abscessus to clinical responses. Using ASCT, we reveal drug tolerance as a distinct genetically encoded bacterial trait conserved across drugs with similar targets and, via genome-wide associations, uncover molecular mechanisms that govern bacterial killing. This study establishes the technical framework and in vivo validation for large-scale bacterial killing assessments to advance our understanding of bacterial survival, antibiotic development and clinical decision-making.

microbiology↗

bioRxiv2024

Onset of infectiousness explains differences in transmissibility across Mycobacterium tuberculosis lineages

Mycobacterium tuberculosis complex (MTBC) lineages show substantial variability in virulence, but the epidemiological consequences of this variability have not been studied in detail. Here, we aimed for a lineage-specific epidemiological characterization by applying phylodynamic models to genomic data from different countries, representing the most abundant MTBC lineages. Our results show that all lineages are associated with similar durations and levels of infectiousness, resulting in similar reproductive numbers. However, L1 and L6 are associated with a delayed onset of infectiousness, leading to longer periods between subsequent transmission events. Together, our findings highlight the role of MTBC phylogenetic diversity in tuberculosis disease progression and transmission.

genomics↗

bioRxiv2024

CXCL9, granzyme B and TNF-alpha orchestrate protective in vitro granulomatous responses across Mycobacterium tuberculosis complex lineages

The members of the Mycobacterium tuberculosis complex (MTBC) causing human tuberculosis comprise ten phylogenetic lineages that differ in their geographical distribution. The human consequences of this phylogenetic diversity remain poorly understood. Here, we assessed the phenotypic properties at the host-pathogen interface of 14 clinical strains representing five major MTBC lineages. Using a human in vitro granuloma model combined with bacterial load assessment, microscopy, flow cytometry, and multiplexed-bead arrays, we observed considerable intra-lineage diversity. Yet, modern lineages were overall associated with increased growth rate and more pronounced granulomatous responses. MTBC lineages exhibited distinct propensities to accumulate triglyceride lipid droplets --a phenotype associated with dormancy-- that was particularly pronounced in lineage 2 and reduced in lineage 3 strains. The most favorable granuloma responses were associated with strong CD4 and CD8 T cell activation as well as inflammatory responses mediated by CXCL9, granzyme B and TNF. Both of which showed consistent negative correlation with bacterial proliferation across genetically distant MTBC strains of different lineages. Taken together, our data indicate that different virulence strategies and protective immune traits associate with MTBC genetic diversity at lineage and strain level.

immunology↗

bioRxiv2024

Large contribution of repeats to genetic variation in a transmission cluster of Mycobacterium tuberculosis

Repeats are the most diverse and dynamic, but also the least well understood component of microbial genomes. For all we know, repeat-associated mutations such as duplications, deletions, inversions, and gene conversion might be as common as point mutations, but because of short-read myopia and methodological bias they have received much less attention. Long-read sequencing opens the perspective of resolving repeats and systematically investigating the mutations they induce. For this study, we assembled the genomes of 16 closely related strains of the bacterial pathogen Mycobacterium tuberculosis from PacBio HiFi reads, with the aim of characterizing the full spectrum of DNA polymorphisms. We find that complete and accurate genomes can be assembled from HiFi reads, with read size being the main limitation in the presence of duplications. By combining a reference-free pangenome graph with extensive repeat annotation, we identified 110 variants, 58 of which can be assigned to repeat-associated mutational mechanisms such as strand slippage and homologous recombination. While recombination events are less frequent than point mutations, they can affect large regions and introduce multiple variants at once, as shown by three gene conversion events and a duplication of 7.3 kb that involve ppe18 and ppe57, two genes possibly involved in immune subversion. Our study shows that the contribution of repeat-associated mechanisms of mutation can be similar to that of point mutations at the microevolutionary scale of an outbreak. A large reservoir of unstudied genetic variation in this "monomorphic" bacterial pathogen awaits investigation.

genomics↗

bioRxiv2023

Bacterial diversity dominates variable macrophage responses of tuberculosis patients in Tanzania

The Mycobacterium tuberculosis complex (MTBC) comprises nine human-adapted lineages that differ in their geographical distribution. Local adaptation of specific MTBC genotypes to the respective human host population has been invoked in this context. Here, we generated macrophages from cryopreserved blood mononuclear cells of Tanzanian tuberculosis patients, from which the infecting MTBC strains had previously been phylogenetically characterized. We infected these macrophages ex vivo with a phylogenetically similar MTBC strain ("matched infection") or with strains representative of other MTBC lineages ("mismatched infection"). We found that L1 infections resulted in a significantly lower bacterial burden and that the intra-cellular replication rate of L2 strains was significantly higher compared the other MTBC lineages, irrespective of the MTBC lineage originally infecting the patients. Moreover, L4-infected macrophages released significantly greater amounts of TNF-, IL-6, IL-10, MIP-1{beta}, and IL-1{beta} compared to macrophages infected by all other strains. Taken together, while our results revealed no measurable effect of local adaptation, they further highlight the strong impact of MTBC phylogenetic diversity on the variable outcome of the host-pathogen interaction in human tuberculosis.

microbiology↗

bioRxiv2023

HIV co-infection is associated with reduced Mycobacterium tuberculosis transmissibility in sub-Saharan Africa

Persons living with HIV are known to be at increased risk of developing tuberculosis (TB) disease upon infection with Mycobacterium tuberculosis (Mtb). However, it has remained unclear how HIV co-infection affects subsequent Mtb transmission from these patients. Here, we customized a Bayesian phylodynamic framework to estimate the effects of HIV co-infection on the Mtb transmission dynamics from sequence data. We applied our model to four Mtb genomic datasets collected in sub-Saharan African countries with a generalized HIV epidemic. Our results confirm that HIV co-infection is a strong risk factor for developing active TB. Additionally, we demonstrate that HIV co-infection is associated with a reduced effective reproductive number for TB. Stratifying the population by CD4+ T-cell count yielded similar results, suggesting that, in this context, CD4+ T-cell count is not a better predictor of Mtb transmissibility than HIV infection status. Together, our genome-based analyses complement observational household studies, and firmly establish the negative association between HIV co-infection and Mtb transmissibility. Author summaryMany sub-Saharan African countries have seen a considerable rise in TB incidence since the introduction of HIV, suggesting a strong interaction between HIV and TB epidemics. HIV infection is recognized as an important risk factor for developing TB, but the contribution of HIV-infected TB patients to further Mtb transmission is poorly understood. In this study, we analyzed four sets of Mtb genomic sequences collected in different countries, including sequences from HIV-negative and HIV-positive TB patients. We applied a phylodynamic model to these sequences, aimed at inferring transmission dynamics within and between different host populations. While our findings support that HIV is a strong risk factor for TB, we show that HIV-positive TB patients generate a significantly lower number of secondary TB cases than HIV-negative patients. This suggests that HIV-positive patients often act as sinks in Mtb transmission chains, while HIV-negative patients are a major source of transmission.

microbiology↗

bioRxiv2021

Using population-specific add-on polymorphisms to improve genotype imputation in underrepresented populations

Genome-wide association studies rely on the statistical inference of untyped variants, called imputation, to increase the coverage of genotyping arrays. However, the results are often suboptimal in populations underrepresented in existing reference panels and array designs, since the selected single nucleotide polymorphisms (SNPs) may fail to capture population-specific haplotype structures, hence the full extent of common genetic variation. Here, we propose to sequence the full genome of a small subset of an underrepresented study cohort to inform the selection of population-specific add-on SNPs, such that the remaining array-genotyped cohort could be more accurately imputed. Using a Tanzania-based cohort as a proof-of-concept, we demonstrate the validity of our approach by showing improvements in imputation accuracy after the addition of our designed addon SNPs to the base H3Africa array.

genetics↗

bioRxiv2020

Local adaptation in populations of Mycobacterium tuberculosis endemic to the Indian Ocean Rim

Lineage 1 (L1) and 3 (L3) are two lineages of the Mycobacterium tuberculosis complex (MTBC), causing tuberculosis (TB) in humans. L1 and L3 are endemic to the Rim of the Indian Ocean, the region that accounts for most of the worlds new TB cases. Despite their relevance for this region, L1 and L3 remain understudied. Here we analyzed 2,938 L1 and 2,030 L3 whole genome sequences originating from 69 countries. We show that South Asia played a central role in the dispersion of these two lineages to neighboring regions. Moreover, we found that L1 exhibits signatures of local adaptation at the esxH locus, a gene coding for a secreted effector that targets the human endosomal sorting complex, and is included in several vaccine candidates. Our study highlights the importance of genetic diversity in the MTBC, and sheds new light on two of the most important MTBC lineages affecting humans.

genomics↗

bioRxiv2020

HIV coinfection is associated with low fitness rpoB variants in rifampicin-resistant Mycobacterium tuberculosis

We analysed 312 drug-resistant genomes of Mycobacterium tuberculosis (Mtb) collected from HIV coinfected and HIV negative TB patients from nine countries with a high tuberculosis burden. We found that rifampicin-resistant Mtb strains isolated from HIV coinfected patients carried disproportionally more resistance-conferring mutations in rpoB that are associated with a low fitness in the absence of the drug, suggesting these low fitness rpoB variants can thrive in the context of reduced host immunity.

evolutionary biology↗

bioRxiv2019

The Evolution of Fluoroquinolone-Resistance in Mycobacterium tuberculosis is Modulated by the Genetic Background

Fluoroquinolones (FQ) form the backbone in experimental treatment regimens against drug-susceptible tuberculosis. However, little is known on whether the genetic variation present in natural populations of Mycobacterium tuberculosis (Mtb) affects the evolution of FQ-resistance (FQ-R). To investigate this question, we used a set of Mtb strains that included nine genetically distinct drug-susceptible clinical isolates, and measured their frequency of resistance to the FQ ofloxacin (OFX) in vitro. We found that the Mtb genetic background led to differences in the frequency of OFX-resistance (OFX-R) that spanned two orders of magnitude and substantially modulated the observed mutational profiles for OFX-R. Further in vitro assays showed that the genetic background also influenced the minimum inhibitory concentration and the fitness effect conferred by a given OFX-R mutation. To test the clinical relevance of our in vitro work, we surveyed the mutational profile for FQ-R in publicly available genomic sequences from clinical Mtb isolates, and found substantial Mtb lineage-dependent variability. Comparison of the clinical and the in vitro mutational profiles for FQ-R showed that 45% and 19% of the variability in the clinical frequency of FQ-R gyrA mutations in Lineage 2 and Lineage 4 strains, respectively, can be attributed to how Mtb evolves FQ-R in vitro. As the Mtb genetic background strongly influenced the evolution of FQ-R in vitro, we conclude that the genetic background of Mtb also impacts the evolution of FQ-R in the clinic.\n\nSignificanceNewer generations of fluoroquinolones form the backbone in many experimental treatment regimens against M. tuberculosis (Mtb). While the genetic variation in natural populations of Mtb can influence resistance evolution to multiple different antibiotics, it is unclear whether it modulates fluoroquinolone-resistance evolution as well. Using a combination of in vitro assays coupled with genomic analysis of clinical isolates, we provide the first evidence illustrating the Mtb genetic backgrounds substantial role in fluoroquinolone-resistance evolution, and highlight the importance of bacterial genetics when studying the prevalence of fluoroquinolone-resistance in Mtb. Our work may provide insights into how to maximize the timespan in which fluoroquinolones remain effective in clinical settings, whether as part of current standardized regimens, or in new regimens against Mtb.

microbiology↗

bioRxiv2018

Resource misallocation as a mediator of fitness costs in antibiotic resistance.

Antimicrobial resistance poses a threat to global health and the economy. It is widely accepted that, in the absence of antibiotics, drug resistance mutations carry a fitness cost. In the case of rifampicin resistance in fast-growing bacteria, this cost stems from a reduced transcription rate of the RNA polymerase resulting in slower ribosome biosynthesis. However, this relationship does not apply in the slow-growing Mycobacterium tuberculosis, where the true mechanism of fitness cost of rifampicin resistance as well as the impact of compensatory evolution remain unknown. Here we show, using global transcriptomic and proteomic profiling of selected M. tuberculosis mutants and clinical strains, that the fitness cost of rifampicin resistance in M. tuberculosis is the result of the physiological burden caused by aberrant gene expression. We further show that the perceived burden can be increased, effectively suppressing the emergence of drug resistance.

microbiology↗

bioRxiv2018

Insights into the genetic diversity of Mycobacterium tuberculosis in Tanzania

BackgroundHuman tuberculosis (TB) is caused by seven phylogenetic lineages of the Mycobacterium tuberculosis complex (MTBC), Lineage 1-7. Recent advances in rapid genotyping of MTBC based on single nucleotide polymorphisms (SNP), allow for rapid and phylogenetically robust strain classification, paving the way for defining genotype-phenotype relationships in clinical settings. Such studies have revealed that, in addition to host and environmental factors, different strains of the MTBC influence the outcome of TB infection and disease. In Tanzania, such molecular epidemiological studies of TB however are scarce in spite of a high TB burden.\n\nMethods and FindingsHere we used a SNP-typing method to genotype a nationwide collection of 2,039 MTBC clinical isolates obtained from new and retreatment TB cases diagnosed in 2012 and 2013. Four lineages, namely Lineage 1-4 were identified. The distribution and frequency of these lineages varied across the regions but overall, Lineage 4 was the most frequent (n=866, 42.5%), followed by Lineage 3 (n=681, 33.4%) and 1 (n=336, 16.5%), with Lineage 2 being the least frequent (n=92, 4.5%). A total of 64 (3.1%) isolates could not be assigned to any lineage. We found Lineage 2 to be associated with female sex (adjusted odds ratio [aOR] 2.25; 95% confidence interval [95% CI] 1.38 - 3.70, p<0.001) and retreatment (aOR 1.78; 95% CI 1.00 - 3.02, p=0.040). We found no associations between MTBC lineage and patient age or HIV status. Our sublineage typing based on spacer oligotyping revealed the presence of mainly EAI, CAS and LAM families. Finally, we detected low levels of multidrug resistant isolates among a subset of retreatment cases\n\nConclusionsThis study provides novel insights into the influence of pathogen-related factors on the TB epidemic in Tanzania.

epidemiology↗

bioRxiv2018

Transition bias influences the evolution of antibiotic resistance in Mycobacterium tuberculosis

Transition bias, an overabundance of transitions relative to transversions, has been widely reported among studies of mutations spreading under relaxed selection. However, demonstrating the role of transition bias in adaptive evolution remains challenging. We addressed this challenge by analyzing adaptive antibiotic-resistance mutations in the major human pathogen Mycobacterium tuberculosis. We found strong evidence for transition bias in two independently curated datasets comprising 152 and 208 antibiotic resistance mutations. This was true at the level of mutational paths (distinct, adaptive DNA sequence changes) and events (individual instances of the adaptive DNA sequence changes), and across different genes and gene promoters conferring resistance to a diversity of antibiotics. It was also true for mutations that do not code for amino acid changes (in gene promoters and the ribosmal gene rrs), and for mutations that are synonymous to each other and are therefore likely to have similar fitness effects, suggesting that transition bias can be caused by a bias in mutation supply. These results point to a central role for transition bias in determining which mutations drive adaptive antibiotic resistance evolution in a key pathogen.\n\nSignificance statementWhether and how transition bias influences adaptive evolution remain open questions. We studied 296 DNA mutations that confer antibiotic resistance to the human pathogen Mycobacterium tuberculosis. We uncovered strong transition bias among these mutations and also among the number of times each mutation has evolved in different strains or geographic locations, demonstrating that transition bias can influence adaptive evolution. For a subset of mutations, we were able to rule out an alternative selection-based hypothesis for this bias, indicating that transition bias can be caused by a biased mutation supply. By revealing this bias among M. Tuberculosis resistance mutations, our findings improve our ability to predict the mutational pathways by which pathogens overcome treatment.

evolutionary biology↗

bioRxiv2018

Whole genome sequencing for drug resistance profile prediction in Mycobacterium tuberculosis

Whole genome sequencing allows rapid detection of drug-resistant M. tuberculosis isolates. However, high-quality data linking quantitative phenotypic drug susceptibility testing (DST) and genomic data have thus far been lacking.\n\nWe determined drug resistance profiles of 176 genetically diverse clinical M. tuberculosis isolates from Democratic Republic of the Congo, Ivory Coast, Peru, Thailand and Switzerland by quantitative phenotypic DST for 11 antituberculous drugs using the BD BACTEC MGIT 960 system and 7H10 agar dilution to generate a cross-validated phenotypic DST readout. We compared phenotypic drug susceptibility results with predicted drug resistance profiles inferred by whole genome sequencing.\n\nBoth phenotypic DST methods identically classified the strains into resistant/susceptible in 73-99% of the cases, depending on the drug. Changes in minimal inhibitory concentrations were readily explained by mutations identified by whole genome sequencing. Using the whole genome sequences we were able to predict quantitative drug resistance levels where wild type and mutant MIC distributions did not overlap. The utility of genome sequences to predict quantitative levels of drug resistance was partially limited due to incompletely understood mechanisms influencing the expression of phenotypic drug resistance. The overall sensitivity and specificity of whole genome-based DST were 86.8% and 94.5%, respectively.\n\nDespite some limitations, whole genome sequencing has high predictive power to infer resistance profiles without the need for time-consuming phenotypic methods.\n\nOne sentence summaryWhole genome sequencing of clinical M. tuberculosis isolates accurately predicts drug resistance profiles and may replace culture-based drug susceptibility testing in the future.

microbiology↗

bioRxiv2018

Reference Set of Mycobacterium tuberculosis Clinical Strains: A tool for research and product development

The Mycobacterium tuberculosis complex (MTBC) causes tuberculosis (TB) in humans and various other mammals. The human-adapted members of the MTBC comprise seven phylogenetic lineages that differ in their geographical distribution. There is growing evidence that this phylogenetic diversity modulates the outcome of TB infection and disease. For decades, TB research and development has focused on the two canonical MTBC reference strains H37Rv and Erdman, both of which belong to Lineage 4. Relying on only a few laboratory-adapted strains can be misleading as study results might not be directly transferrable to clinical settings where patients are infected with a diverse array of strains, including drug-resistant variants. Here, we argue for the need to expand TB research and development by incorporating the phylogenetic diversity of the MTBC. To facilitate such work, we have assembled a group of 20 genetically well-characterized clinical strains representing the seven known human-adapted MTBC lineages. With the \"MTBC clinical strains reference set\" we aim to provide a standardized resource for the TB community. We hope it will enable more direct comparisons between studies that explore the physiology of MTBC beyond the lab strains used thus far. We anticipate that detailed phenotypic analyses of this reference strain set will increase our understanding of TB biology and assist in the development of new control tools that are universally effective.

microbiology↗

bioRxiv2018

A New Phylogenetic Framework for the Animal-adapted Mycobacterium tuberculosis Complex

Tuberculosis (TB) affects humans and other animals and is caused by bacteria from the Mycobacterium tuberculosis complex (MTBC). Previous studies have shown that there are at least nine members of the MTBC infecting animals other than humans; these have also been referred to as ecotypes. However, the ecology and the evolution of these animal-adapted MTBC ecotypes are poorly understood. Here we screened 12,886 publicly available MTBC genomes and newly sequenced 17 animal-adapted MTBC strains, gathering a total of 529 genomes of animal-adapted MTBC strains. Phylogenomic and comparative analyses confirm that the animal-adapted MTBC members are paraphyletic with some members more closely related to the human-adapted Mycobacterium africanum Lineage 6 than to other animal-adapted strains. Furthermore, we identified four main animal-adapted MTBC clades that might correspond to four main host shifts; two of these clades are proposed to reflect independent cattle domestication events. Contrary to what would be expected from an obligate pathogen, MTBC nucleotide diversity was not positively correlated with host phylogenetic distances, suggesting that host tropism in the animal-adapted MTBC seems to be driven more by contact rates and demographic aspects of the host population rather than host relatedness. By combining phylogenomics with ecological data, we propose an evolutionary scenario in which the ancestor of Lineage 6 and all animal-adapted MTBC ecotypes was a generalist pathogen that subsequently adapted to different host species. This study provides a new phylogenetic framework to better understand the evolution of the different ecotypes of the MTBC and guide future work aimed at elucidating the molecular mechanisms underlying host specificity.

evolutionary biology↗

bioRxiv2018

Drug susceptibility testing and mortality in patients treated for tuberculosis in high-burden countries

BackgroundDrug resistance and HIV co-infection are challenges for the global control of tuberculosis.\n\nMethodsWe collected Mycobacterium tuberculosis isolates from adult patients in Cote dIvoire, Democratic Republic of the Congo, Kenya, Nigeria, South Africa, Peru, and Thailand, stratified by HIV status and tuberculosis drug resistance. Molecular or phenotypic drug susceptibility testing (DST) was done locally and at the Swiss tuberculosis reference laboratory. We examined mortality during treatment according to DST results and treatment adequacy in logistic regression models adjusting for sex, age, sputum microscopy and HIV status.\n\nFindings634 tuberculosis patients were included; median age was 33.2 years, 239 (37.7%) were female, 272 (42.9%) HIV-positive and 69 (10.9%) patients died. Based on the reference laboratory DST, 394 (62.2%) strains were pan-susceptible, 45 (7.1%) mono-resistant, 163 (25.7%) multidrug-resistant (MDR-TB), and 30 (4.7%) had pre-extensive or extensive drug resistance (pre-XDR/XDR-TB). Results of reference and local laboratories were discordant in 121 (19.1%) cases, corresponding to a sensitivity of 84.3% and a specificity of 90.8%. In patients with drug-resistant tuberculosis, discordant results were associated with increased mortality (risk ratio 1.81; 95% CI 1.07-3.07). In logistic regression, compared to adequately treated patients with pan-susceptible strains, the adjusted odds ratio for death was 4.23 (95% CI 2.16-8.29) for adequately treated patients with drug-resistant strains and 21.54 (95% CI 3.36-138.1) for inadequately treated patients with drug-resistant strains. HIV status was not associated with mortality.\n\nInterpretationUsing a reference laboratory standard, inaccurate DST leading to inappropriate treatment of drug-resistant tuberculosis, but not HIV infection, contributed to mortality.

epidemiology↗