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 alone. Together, our genome-based analyses complement observational household contact studies, and more firmly establish the negative association between HIV co-infection and Mtb transmissibility.

Back-to-Africa introductions of Mycobacterium tuberculosis as the main cause of tuberculosis in Dar es Salaam, Tanzania.

In settings with high tuberculosis (TB) endemicity, distinct genotypes of the Mycobacterium tuberculosis complex (MTBC) often differ in prevalence. However, the factors leading to these differences remain poorly understood. Here we studied the MTBC population in Dar es Salaam, Tanzania over a six-year period, using 1,082 unique patient-derived MTBC whole-genome sequences (WGS) and associated clinical data. We show that the TB epidemic in Dar es Salaam is dominated by multiple MTBC genotypes introduced to Tanzania from different parts of the world during the last 300 years. The most common MTBC genotypes deriving from these introductions exhibited differences in transmission rates and in the duration of the infectious period, but little differences in overall fitness, as measured by the effective reproductive number. Moreover, measures of disease severity and bacterial load indicated no differences in virulence between these genotypes during active TB. Instead, the combination of an early introduction and a high transmission rate accounted for the high prevalence of L3.1.1, the most dominant MTBC genotype in this setting. Yet, a longer co-existence with the host population did not always result in a higher transmission rate, suggesting that distinct life-history traits have evolved in the different MTBC genotypes. Taken together, our results point to bacterial factors as important determinants of the TB epidemic in Dar es Salaam.

Population Bottlenecks Strongly Affect the Evolutionary Dynamics of Antibiotic Persistence.

Bacterial persistence is a potential cause of antibiotic therapy failure. Antibiotic-tolerant persisters originate from phenotypic differentiation within a susceptible population, occurring with a frequency that can be altered by mutations. Recent studies have proven that persistence is a highly evolvable trait and, consequently, an important evolutionary strategy of bacterial populations to adapt to high-dose antibiotic therapy. Yet, the factors that govern the evolutionary dynamics of persistence are currently poorly understood. Theoretical studies predict far-reaching effects of bottlenecking on the evolutionary adaption of bacterial populations, but these effects have never been investigated in the context of persistence. Bottlenecking events are frequently encountered by infecting pathogens during host-to-host transmission and antibiotic treatment. In this study, we used a combination of experimental evolution and barcoded knockout libraries to examine how population bottlenecking affects the evolutionary dynamics of persistence. In accordance with existing hypotheses, small bottlenecks were found to restrict the adaptive potential of populations and result in more heterogeneous evolutionary outcomes. Evolutionary trajectories followed in small-bottlenecking regimes additionally suggest that the fitness landscape associated with persistence has a rugged topography, with distinct trajectories toward increased persistence that are accessible to evolving populations. Furthermore, sequencing data of evolved populations and knockout libraries after selection reveal various genes that are potentially involved in persistence, including previously known as well as novel targets. Together, our results do not only provide experimental evidence for evolutionary theories, but also contribute to a better understanding of the environmental and genetic factors that guide bacterial adaptation to antibiotic treatment.

General Mechanisms Leading to Persister Formation and Awakening.

All bacterial populations harbor a small fraction of transiently antibiotic-tolerant cells called persisters. These phenotypic variants compromise successful antibiotic treatment because they are held responsible for the relapse of many chronic infections. In addition, studies employing experimental evolution have demonstrated that persistence contributes to the development of antibiotic resistance. Persisters are typically described as dormant cells. However, recent findings indicate a role for active mechanisms in the formation and maintenance of the persister phenotype. This review summarizes novel insights into the molecular mechanisms of persister formation and awakening, focusing on changes in cell physiology mediated by persistence effectors.

Bacteria under antibiotic attack: Different strategies for evolutionary adaptation.

Bacteria are well known for their extremely high adaptability in stressful environments. The clinical relevance of this property is clearly illustrated by the ever-decreasing efficacy of antibiotic therapies. Frequent exposures to antibiotics favor bacterial strains that have acquired mechanisms to overcome drug inhibition and lethality. Many strains, including life-threatening pathogens, exhibit increased antibiotic resistance or tolerance, which considerably complicates clinical practice. Alarmingly, recent studies show that in addition to resistance, tolerance levels of bacterial populations are extremely flexible in an evolutionary context. Here, we summarize laboratory studies providing insight in the evolution of resistance and tolerance and shed light on how the treatment conditions could affect the direction of bacterial evolution under antibiotic stress.

Antibiotic dose and nutrient availability differentially drive the evolution of antibiotic resistance and persistence.

Effective treatment of bacterial infections proves increasingly challenging due to the emergence of bacterial variants that endure antibiotic exposure. Antibiotic resistance and persistence have been identified as two major bacterial survival mechanisms, and several studies have shown a rapid and strong selection of resistance or persistence mutants under repeated drug treatment. Yet, little is known about the impact of the environmental conditions on resistance and persistence evolution and the potential interplay between both phenotypes. Based on the distinct growth and survival characteristics of resistance and persistence mutants, we hypothesized that the antibiotic dose and availability of nutrients during treatment might play a key role in the evolutionary adaptation to antibiotic stress. To test this hypothesis, we combined high-throughput experimental evolution with a mathematical model of bacterial evolution under intermittent antibiotic exposure. We show that high nutrient levels during antibiotic treatment promote selection of high-level resistance, but that resistance mainly emerges independently of persistence when the antibiotic concentration is sufficiently low. At higher doses, resistance evolution is facilitated by the preceding or concurrent selection of persistence mutants, which ensures survival of populations in harsh conditions. Collectively, our experimental data and mathematical model elucidate the evolutionary routes toward increased bacterial survival under different antibiotic treatment schedules, which is key to designing effective antibiotic therapies.

The relative transmission fitness of multidrug-resistant Mycobacterium tuberculosis in a drug resistance hotspot.

Multidrug-resistant tuberculosis (MDR-TB) is among the most frequent causes of death due to antimicrobial resistance. Although only 3% of global TB cases are MDR, geographical hotspots with up to 40% of MDR-TB have been observed in countries of the former Soviet Union. While the quality of TB control and patient-related factors are known contributors to such hotspots, the role of the pathogen remains unclear. Here we show that in the country of Georgia, a known hotspot of MDR-TB, MDR Mycobacterium tuberculosis strains of lineage 4 (L4) transmit less than their drug-susceptible counterparts, whereas most MDR strains of L2 suffer no such defect. Our findings further indicate that the high transmission fitness of these L2 strains results from epistatic interactions between the rifampicin resistance-conferring mutation RpoB S450L, compensatory mutations in the RNA polymerase, and other pre-existing genetic features of L2/Beijing clones that circulate in Georgia. We conclude that the transmission fitness of MDR M. tuberculosis strains is heterogeneous, but can be as high as drug-susceptible forms, and that such highly drug-resistant and transmissible strains contribute to the emergence and maintenance of hotspots of MDR-TB. As these strains successfully overcome the metabolic burden of drug resistance, and given the ongoing rollout of new treatment regimens against MDR-TB, proper surveillance should be implemented to prevent these strains from acquiring resistance to the additional drugs.

Enrichment of Persister Cells Through Β-Lactam-Induced Filamentation and Size Separation.

Analyzing persisters at the single-cell level is crucial to properly define their phenotypic traits. However, single-cell analyses are challenging due to the rare and temporary nature of persister cells, thus requiring their rapid and efficient enrichment in a culture. Existing methods to isolate persisters from a bacterial population show important shortcomings, including contamination with susceptible cells and/or cell debris, which complicate subsequent microscopic analyses. We here describe a protocol to enrich persisters in a culture using ß-lactam-induced filamentation followed by size separation. This protocol minimizes the amount of cell debris in the final sample, facilitating single-cell studies of persister cells.

Antibiotics: Combatting Tolerance To Stop Resistance.

Antibiotic resistance poses an alarming and ever-increasing threat to modern health care. Although the current antibiotic crisis is widely acknowledged, actions taken so far have proved insufficient to slow down the rampant spread of resistant pathogens. Problematically, routine screening methods and strategies to restrict therapy failure almost exclusively focus on genetic resistance, while evidence for dangers posed by other bacterial survival strategies is mounting. Antibiotic tolerance, occurring either population-wide or in a subpopulation of cells, allows bacteria to transiently overcome antibiotic treatment and is overlooked in clinical practice. In addition to prolonging treatment and causing relapsing infections, recent studies have revealed that tolerance also accelerates the emergence of resistance. These critical findings emphasize the need for strategies to combat tolerance, not only to improve treatment of recurrent infections but also to effectively address the problem of antibiotic resistance at the root.

Bacterial persistence promotes the evolution of antibiotic resistance by increasing survival and mutation rates.

Persisters are transiently antibiotic-tolerant cells that complicate the treatment of bacterial infections. Both theory and experiments have suggested that persisters facilitate genetic resistance by constituting an evolutionary reservoir of viable cells. Here, we provide evidence for a strong positive correlation between persistence and the likelihood to become genetically resistant in natural and lab strains of E. coli. This correlation can be partly attributed to the increased availability of viable cells associated with persistence. However, our data additionally show that persistence is pleiotropically linked with mutation rates. Our theoretical model further demonstrates that increased survival and mutation rates jointly affect the likelihood of evolving clinical resistance. Overall, these results suggest that the battle against antibiotic resistance will benefit from incorporating anti-persister therapies.

Enrichment of persisters enabled by a ß-lactam-induced filamentation method reveals their stochastic single-cell awakening.

When exposed to lethal doses of antibiotics, bacterial populations are most often not completely eradicated. A small number of phenotypic variants, defined as 'persisters', are refractory to antibiotics and survive treatment. Despite their involvement in relapsing infections, processes determining phenotypic switches from and to the persister state largely remain elusive. This is mainly due to the low frequency of persisters and the lack of reliable persistence markers, both hampering studies of persistence at the single-cell level. Here we present a highly effective persister enrichment method involving cephalexin, an antibiotic that induces extensive filamentation of susceptible cells. We used our enrichment method to monitor outgrowth of Escherichia coli persisters at the single-cell level, thereby conclusively demonstrating that persister awakening is a stochastic phenomenon. We anticipate that our approach can have far-reaching consequences in the persistence field, by allowing single-cell studies at a much higher throughput than previously reported.

Frequency of antibiotic application drives rapid evolutionary adaptation of Escherichia coli persistence.

The evolution of antibiotic resistance is a major threat to society and has been predicted to lead to 10 million casualties annually by 2050(1). Further aggravating the problem, multidrug tolerance in bacteria not only relies on the build-up of resistance mutations, but also on some cells epigenetically switching to a non-growing antibiotic-tolerant 'persister' state(2-6). Yet, despite its importance, we know little of how persistence evolves in the face of antibiotic treatment(7). Our evolution experiments in Escherichia coli demonstrate that extremely high levels of multidrug tolerance (20-100%) are achieved by single point mutations in one of several genes and readily emerge under conditions approximating clinical, once-daily dosing schemes. In contrast, reversion to low persistence in the absence of antibiotic treatment is relatively slow and only partially effective. Moreover, and in support of previous mathematical models(8-10), we show that bacterial persistence quickly adapts to drug treatment frequency and that the observed rates of switching to the persister state can be understood in the context of 'bet-hedging' theory. We conclude that persistence is a major component of the evolutionary response to antibiotics that urgently needs to be considered in both diagnostic testing and treatment design in the battle against multidrug tolerance.