Genetics and roadblocks of drug resistant tuberculosis

Considering the extensive evolutionary history of Mycobacterium tuberculosis, anti-Tuberculosis (TB) drug therapy exerts a recent selective pressure. However, in a microorganism devoid of horizontal gene transfer and with a strictly clonal populational structure such as M. tuberculosis the usual, but not sole, path to overcome drug susceptibility is through de novo mutations on a relatively strict set of genes. The possible allelic diversity that can be associated with drug resistance through several mechanisms such as target alteration or target overexpression, will dictate how these genes can become associated with drug resistance. The success demonstrated by this pathogenic microbe in this latter process and its ability to spread is currently one of the major obstacles to an effective TB elimination. This article reviews the action mechanism of the more important anti-TB drugs, including bedaquiline and delamanid, along with new findings on specific resistance mechanisms. With the development, validation and endorsement of new in vitro molecular tests for drug resistance, knowledge on these resistance mechanisms and microevolutionary dynamics leading to the emergence and fixation of drug resistance mutations within the host is highly important. Additionally, the fitness toll imposed by resistance development is also herein discussed together with known compensatory mechanisms. By elucidating the possible mechanisms that enable one strain to reacquire the original fitness levels, it will be theoretically possible to make more informed decisions and develop novel strategies that can force M. tuberculosis microevolutionary trajectory down through a path of decreasing fitness levels.

Modelling the effects of bacterial cell state and spatial location on tuberculosis treatment: Insights from a hybrid multiscale cellular automaton model

If improvements are to be made in tuberculosis (TB) treatment, an increased understanding of disease in the lung is needed. Studies have shown that bacteria in a less metabolically active state, associated with the presence of lipid bodies, are less susceptible to antibiotics, and recent results have highlighted the disparity in concentration of different compounds into lesions. Treatment success therefore depends critically on the responses of the individual bacteria that constitute the infection. We propose a hybrid, individual-based approach that analyses spatio-temporal dynamics at the cellular level, linking the behaviour of individual bacteria and host cells with the macroscopic behaviour of the microenvironment. The individual elements (bacteria, macrophages and T cells) are modelled using cellular automaton (CA) rules, and the evolution of oxygen, drugs and chemokine dynamics are incorporated in order to study the effects of the microenvironment in the pathological lesion. We allow bacteria to switch states depending on oxygen concentration, which affects how they respond to treatment. This is the first multiscale model of its type to consider both oxygen-driven phenotypic switching of the Mycobacterium tuberculosis and antibiotic treatment. Using this model, we investigate the role of bacterial cell state and of initial bacterial location on treatment outcome. We demonstrate that when bacteria are located further away from blood vessels, less favourable outcomes are more likely, i.e. longer time before infection is contained/cleared, treatment failure or later relapse. We also show that in cases where bacteria remain at the end of simulations, the organisms tend to be slower-growing and are often located within granulomas, surrounded by caseous material.

Caracterización clínica y terapéutica de pacientes con tuberculosis pulmonar en Cali

Objetivo: Establecer las características clínicas, sociodemográficas y farmacológicas de pacientes con tuberculosis pulmonar.Metodología: Se realizó un estudio descriptivo, retrospectivo y de corte transversal con una muestra de 157 pacientes. La información se recolectó de la base de datos de la Secretaría de Salud Pública Municipal de la ciudad de Cali durante el año 2013. La asociación entre las variables se estableció mediante la prueba de chi cuadrado empleando el paquete estadístico SPSS Vs 22.0.Resultados: El 62,4% de los pacientes objeto de estudio eran hombres jóvenes y el 72% de estratos socioeconómicos bajos. El 9,2% de los pacientes presentaron tuberculosis pulmonar farmacorresistente (p = 0,0231). La resistencia a la isoniazida fue de 94,2%; a la rifampicina, de 78,8%; a la pirazinamida, de 21,2%; al etambutol, de 25%; y a la estreptomicina, de 48,1%. Los pacientes desnutridos y adictos a las drogas o al alcohol revelaron mayor resistencia a la terapia antituberculosa. Los pacientes con tuberculosis pulmonar farmacorresistente y adictos a sustancias psicoactivas o al alcohol representaron el 19,2%, con diabetes el 15,4% y los coinfectados con el virus de la inmunodeficiencia humana (VIH), el 13,4%.Conclusiones. La alta proporción de hombres con tuberculosis puede estar condicionada a una mayor exposición al agente por ser el grupo más activo laboralmente. Se evidenció una mayor prevalencia de cepas multirresistentes a fármacos de primera línea en pacientes de estratos socioeconómicamente bajos, de grupos marginados y con factores de riesgo como desnutrición y abuso de alcohol y de sustancias psicoactivas.

Whole Genome Sequence Analysis of a Large Isoniazid-Resistant Tuberculosis Outbreak in London: A Retrospective Observational Study

BACKGROUND

A large isoniazid-resistant tuberculosis outbreak centred on London, United Kingdom, has been ongoing since 1995. The aim of this study was to investigate the power and value of whole genome sequencing (WGS) to resolve the transmission network compared to current molecular strain typing approaches, including analysis of intra-host diversity within a specimen, across body sites, and over time, with identification of genetic factors underlying the epidemiological success of this cluster.

METHODS AND FINDINGS

We sequenced 344 outbreak isolates from individual patients collected over 14 y (2 February 1998-22 June 2012). This demonstrated that 96 (27.9%) were indistinguishable, and only one differed from this major clone by more than five single nucleotide polymorphisms (SNPs). The maximum number of SNPs between any pair of isolates was nine SNPs, and the modal distance between isolates was two SNPs. WGS was able to reveal the direction of transmission of tuberculosis in 16 cases within the outbreak (4.7%), including within a multidrug-resistant cluster that carried a rare rpoB mutation associated with rifampicin resistance. Eleven longitudinal pairs of patient pulmonary isolates collected up to 48 mo apart differed from each other by between zero and four SNPs. Extrapulmonary dissemination resulted in acquisition of a SNP in two of five cases. WGS analysis of 27 individual colonies cultured from a single patient specimen revealed ten loci differed amongst them, with a maximum distance between any pair of six SNPs. A limitation of this study, as in previous studies, is that indels and SNPs in repetitive regions were not assessed due to the difficulty in reliably determining this variation.

CONCLUSIONS

Our study suggests that (1) certain paradigms need to be revised, such as the 12 SNP distance as the gold standard upper threshold to identify plausible transmissions; (2) WGS technology is helpful to rule out the possibility of direct transmission when isolates are separated by a substantial number of SNPs; (3) the concept of a transmission chain or network may not be useful in institutional or household settings; (4) the practice of isolating single colonies prior to sequencing is likely to lead to an overestimation of the number of SNPs between cases resulting from direct transmission; and (5) despite appreciable genomic diversity within a host, transmission of tuberculosis rarely results in minority variants becoming dominant. Thus, whilst WGS provided some increased resolution over variable number tandem repeat (VNTR)-based clustering, it was insufficient for inferring transmission in the majority of cases.

Genetic variation in Mycobacterium tuberculosis isolates from a London outbreak associated with isoniazid resistance

BACKGROUND

The largest outbreak of isoniazid-resistant (INH-R) Mycobacterium tuberculosis in Western Europe is centred in North London, with over 400 cases diagnosed since 1995. In the current study, we evaluated the genetic variation in a subset of clinical samples from the outbreak with the hypothesis that these isolates have unique biological characteristics that have served to prolong the outbreak.

METHODS

Fitness assays, mutation rate estimation, and whole-genome sequencing were performed to test for selective advantage and compensatory mutations.

RESULTS

This detailed analysis of the genetic variation of these INH-R samples suggests that this outbreak consists of successful, closely related, circulating strains with heterogeneous resistance profiles and little or no associated fitness cost or impact on their mutation rate.

CONCLUSIONS

Specific deletions and SNPs could be a peculiar feature of these INH-R M. tuberculosis isolates, and could potentially explain their persistence over the years.

Systems Medicine and Infection

By using a systems-based approach, mathematical and computational techniques can be used to develop models that describe the important mechanisms involved in infectious diseases. An iterative approach to model development allows new discoveries to continually improve the model and ultimately increase the accuracy of predictions.SIR models are used to describe epidemics, predicting the extent and spread of disease. Genome-wide genotyping and sequencing technologies can be used to identify the biological mechanisms behind diseases. These tools help to build strategies for disease prevention and treatment, an example being the recent outbreak of Ebola in West Africa where these techniques were deployed.HIV is a complex disease where much is still to be learned about the virus and the best effective treatment. With basic mathematical modeling techniques, significant discoveries have been made over the last 20 years. With recent technological advances, the computational resources now available, and interdisciplinary cooperation, further breakthroughs are inevitable.In TB, modeling has traditionally been empirical in nature, with clinical data providing the fuel for this top-down approach. Recently, projects have begun to use data derived from laboratory experiments and clinical trials to create mathematical models that describe the mechanisms responsible for the disease.A systems medicine approach to infection modeling helps identify important biological questions that then direct future experiments, the results of which improve the model in an iterative cycle. This means that data from several model systems can be integrated and synthesized to explore complex biological systems.

Shared characteristics between Mycobacterium tuberculosis and fungi contribute to virulence

Mycobacterium tuberculosis, an etiologic agent of tuberculosis, exacts a heavy toll in terms of human morbidity and mortality. Although an ancient disease, new strains are emerging as human population density increases. The emergent virulent strains appear adept at steering the host immune response from a protective Th1 type response towards a Th2 bias, a feature shared with some pathogenic fungi. Other common characteristics include infection site, metabolic features, the composition and display of cell surface molecules, the range of innate immune receptors engaged during infection, and the ability to form granulomas. Literature from these two distinct fields of research are reviewed to propose that the emergent virulent strains of M. tuberculosis are in the process of convergent evolution with pathogenic fungi, and are increasing the prominence of conserved traits from environmental phylogenetic ancestors that facilitate their evasion of host defenses and dissemination.

Limits to compensatory adaptation and the persistence of antibiotic resistance in pathogenic bacteria

Antibiotic resistance carries a fitness cost that could potentially limit the spread of resistance in bacterial pathogens. In spite of this cost, a large number of experimental evolution studies have found that resistance is stably maintained in the absence of antibiotics as a result of compensatory evolution. Clinical studies, on the other hand, have found that resistance in pathogen populations usually declines after antibiotic use is stopped, suggesting that compensatory adaptation is not effective in vivo. In this article, we argue that this disagreement arises because there are limits to compensatory adaptation in nature that are not captured by the design of current laboratory selection experiments. First, clinical treatment fails to eradicate antibiotic-sensitive strains, and competition between sensitive and resistant strains leads to the rapid loss of resistance following treatment. Second, laboratory studies overestimate the efficacy of compensatory adaptation in nature by failing to capture costs associated with compensatory mutations. Taken together, these ideas can potentially reconcile evolutionary theory with the clinical dynamics of antibiotic resistance and guide the development of strategies for containing resistance in clinical pathogens.

Recombinant bacille Calmette-Guerin coexpressing Ag85b, CFP10, and interleukin-12 elicits effective protection against Mycobacterium tuberculosis

BACKGROUND

The tuberculosis (TB) pandemic remains a leading cause of human morbidity and mortality, despite widespread use of the only licensed anti-TB vaccine, bacille Calmette-Guerin (BCG). The protective efficacy of BCG in preventing pulmonary TB is highly variable; therefore, an effective new vaccine is urgently required.

METHODS

In the present study, we assessed the ability of novel recombinant BCG vaccine (rBCG) against Mycobacterium tuberculosis by using modern immunological methods.

RESULTS

Enzyme-linked immunospot assays demonstrated that the rBCG vaccine, which coexpresses two mycobacterial antigens (Ag85B and CFP10) and human interleukin (IL)-12 (rBCG2) elicits greater interferon-γ (IFN-γ) release in the mouse lung and spleen, compared to the parental BCG. In addition, rBCG2 triggers a Th1-polarized response. Our results also showed that rBCG2 vaccination significantly limits M. tuberculosis H37Rv multiplication in macrophages. The rBCG2 vaccine surprisingly induces significantly higher tumor necrosis factor-α (TNF-α) production by peripheral blood mononuclear cells that were exposed to a nonmycobacterial stimulus, compared to the parental BCG.

CONCLUSION

In this study, we demonstrated that the novel rBCG2 vaccine may be a promising candidate vaccine against M. tuberculosis infection.