The impact of nutritional state on the duration of sputum positivity of Mycobacterium tuberculosis

2015 ◽  
Vol 19 (11) ◽  
pp. 1369-1375 ◽  
Author(s):  
K. Hatsuda ◽  
M. Takeuchi ◽  
K. Ogata ◽  
Y. Sasaki ◽  
T. Kagawa ◽  
...  
2016 ◽  
Vol 213 (5) ◽  
pp. 809-825 ◽  
Author(s):  
Yancheng Liu ◽  
Shumin Tan ◽  
Lu Huang ◽  
Robert B. Abramovitch ◽  
Kyle H. Rohde ◽  
...  

Successful chemotherapy against Mycobacterium tuberculosis (Mtb) must eradicate the bacterium within the context of its host cell. However, our understanding of the impact of this environment on antimycobacterial drug action remains incomplete. Intriguingly, we find that Mtb in myeloid cells isolated from the lungs of experimentally infected mice exhibit tolerance to both isoniazid and rifampin to a degree proportional to the activation status of the host cells. These data are confirmed by in vitro infections of resting versus activated macrophages where cytokine-mediated activation renders Mtb tolerant to four frontline drugs. Transcriptional analysis of intracellular Mtb exposed to drugs identified a set of genes common to all four drugs. The data imply a causal linkage between a loss of fitness caused by drug action and Mtb’s sensitivity to host-derived stresses. Interestingly, the environmental context exerts a more dominant impact on Mtb gene expression than the pressure on the drugs’ primary targets. Mtb’s stress responses to drugs resemble those mobilized after cytokine activation of the host cell. Although host-derived stresses are antimicrobial in nature, they negatively affect drug efficacy. Together, our findings demonstrate that the macrophage environment dominates Mtb’s response to drug pressure and suggest novel routes for future drug discovery programs.


AIDS ◽  
2015 ◽  
Vol 29 (2) ◽  
pp. 155-165 ◽  
Author(s):  
Christine E. Jones ◽  
Anneke C. Hesseling ◽  
Nontobeko G. Tena-Coki ◽  
Thomas J. Scriba ◽  
Novel N. Chegou ◽  
...  

2018 ◽  
Vol 4 (suppl_1) ◽  
Author(s):  
Anastasia Koch ◽  
Daniela Brites ◽  
David Stucki ◽  
Joanna C Evans ◽  
Ronnett Seldon ◽  
...  

2020 ◽  
Vol 12 (2) ◽  
pp. 147-159
Author(s):  
Madhulata Kumari ◽  
Neeraj Tiwari ◽  
Naidu Subbarao

Aim: We applied genetic programming approaches to understand the impact of descriptors on inhibitory effects of serine protease inhibitors of Mycobacterium tuberculosis ( Mtb) and the discovery of new inhibitors as drug candidates. Materials & methods: The experimental dataset of serine protease inhibitors of Mtb descriptors was optimized by genetic algorithm (GA) along with the correlation-based feature selection (CFS) in order to develop predictive models using machine-learning algorithms. The best model was deployed on a library of 918 phytochemical compounds to screen potential serine protease inhibitors of  Mtb. Quality and performance of the predictive models were evaluated using various standard statistical parameters. Result: The best random forest model with CFS-GA screened 126 anti-tubercular agents out of 918 phytochemical compounds. Also, genetic programing symbolic classification method is optimized descriptors and developed an equation for mathematical models. Conclusion: The use of CFS-GA with random forest-enhanced classification accuracy and predicted new serine protease inhibitors of Mtb, which can be used for better drug development against tuberculosis.


2020 ◽  
Vol 202 (9) ◽  
Author(s):  
Tien G. Nguyen ◽  
Diego A. Vargas-Blanco ◽  
Louis A. Roberts ◽  
Scarlet S. Shell

ABSTRACT Regulation of gene expression is critical for Mycobacterium tuberculosis to tolerate stressors encountered during infection and for nonpathogenic mycobacteria such as Mycobacterium smegmatis to survive environmental stressors. Unlike better-studied models, mycobacteria express ∼14% of their genes as leaderless transcripts. However, the impacts of leaderless transcript structures on mRNA half-life and translation efficiency in mycobacteria have not been directly tested. For leadered transcripts, the contributions of 5′ untranslated regions (UTRs) to mRNA half-life and translation efficiency are similarly unknown. In M. tuberculosis and M. smegmatis, the essential sigma factor, SigA, is encoded by a transcript with a relatively short half-life. We hypothesized that the long 5′ UTR of sigA causes this instability. To test this, we constructed fluorescence reporters and measured protein abundance, mRNA abundance, and mRNA half-life and calculated relative transcript production rates. The sigA 5′ UTR conferred an increased transcript production rate, shorter mRNA half-life, and decreased apparent translation rate compared to a synthetic 5′ UTR commonly used in mycobacterial expression plasmids. Leaderless transcripts appeared to be translated with similar efficiency as those with the sigA 5′ UTR but had lower predicted transcript production rates. A global comparison of M. tuberculosis mRNA and protein abundances failed to reveal systematic differences in protein/mRNA ratios for leadered and leaderless transcripts, suggesting that variability in translation efficiency is largely driven by factors other than leader status. Our data are also discussed in light of an alternative model that leads to different conclusions and suggests leaderless transcripts may indeed be translated less efficiently. IMPORTANCE Tuberculosis, caused by Mycobacterium tuberculosis, is a major public health problem killing 1.5 million people globally each year. During infection, M. tuberculosis must alter its gene expression patterns to adapt to the stress conditions it encounters. Understanding how M. tuberculosis regulates gene expression may provide clues for ways to interfere with the bacterium’s survival. Gene expression encompasses transcription, mRNA degradation, and translation. Here, we used Mycobacterium smegmatis as a model organism to study how 5′ untranslated regions affect these three facets of gene expression in multiple ways. We furthermore provide insight into the expression of leaderless mRNAs, which lack 5′ untranslated regions and are unusually prevalent in mycobacteria.


Vaccines ◽  
2020 ◽  
Vol 8 (1) ◽  
pp. 67 ◽  
Author(s):  
Sanne Burkert ◽  
Ralf R. Schumann

Tuberculosis (TB) is still an important global threat and although the causing organism has been discovered long ago, effective prevention strategies are lacking. Mycobacterium tuberculosis (MTB) is a unique pathogen with a complex host interaction. Understanding the immune responses upon infection with MTB is crucial for the development of new vaccination strategies and therapeutic targets for TB. Recently, it has been proposed that sensing bacterial nucleic acid in antigen-presenting cells via intracellular pattern recognition receptors (PRRs) is a central mechanism for initiating an effective host immune response. Here, we summarize key findings of the impact of mycobacterial RNA sensing for innate and adaptive host immunity after MTB infection, with emphasis on endosomal toll-like receptors (TLRs) and cytosolic sensors such as NLRP3 and RLRs, modulating T-cell differentiation through IL-12, IL-21, and type I interferons. Ultimately, these immunological pathways may impact immune memory and TB vaccine efficacy. The novel findings described here may change our current understanding of the host response to MTB and potentially impact clinical research, as well as future vaccination design. In this review, the current state of the art is summarized, and an outlook is given on how progress can be made.


mBio ◽  
2019 ◽  
Vol 10 (3) ◽  
Author(s):  
Sivaranjani Namasivayam ◽  
Keith D. Kauffman ◽  
John A. McCulloch ◽  
Wuxing Yuan ◽  
Vishal Thovarai ◽  
...  

ABSTRACT The factors that determine host susceptibility to tuberculosis (TB) are poorly defined. The microbiota has been identified as a key influence on the nutritional, metabolic, and immunological status of the host, although its role in the pathogenesis of TB is currently unclear. Here, we investigated the influence of Mycobacterium tuberculosis exposure on the microbiome and conversely the impact of the intestinal microbiome on the outcome of M. tuberculosis exposure in a rhesus macaque model of tuberculosis. Animals were infected with different strains and doses of M. tuberculosis in three independent experiments, resulting in a range of disease severities. The compositions of the microbiotas were then assessed using a combination of 16S rRNA and metagenomic sequencing in fecal samples collected pre- and postinfection. Clustering analyses of the microbiota compositions revealed that alterations in the microbiome after M. tuberculosis infection were of much lower magnitude than the variability seen between individual monkeys. However, the microbiomes of macaques that developed severe disease were noticeably distinct from those of the animals with less severe disease as well as from each other. In particular, the bacterial families Lachnospiraceae and Clostridiaceae were enriched in monkeys that were more susceptible to infection, while numbers of Streptococcaceae were decreased. These findings in infected nonhuman primates reveal that certain baseline microbiome communities may strongly associate with the development of severe tuberculosis following infection and can be more important disease correlates than alterations to the microbiota following M. tuberculosis infection itself. IMPORTANCE Why some but not all individuals infected with Mycobacterium tuberculosis develop disease is poorly understood. Previous studies have revealed an important influence of the microbiota on host resistance to infection with a number of different disease agents. Here, we investigated the possible role of the individual’s microbiome in impacting the outcome of M. tuberculosis infection in rhesus monkeys experimentally exposed to this important human pathogen. Although M. tuberculosis infection itself caused only minor alterations in the composition of the gut microbiota in these animals, we observed a significant correlation between an individual monkey’s microbiome and the severity of pulmonary disease. More importantly, this correlation between microbiota structure and disease outcome was evident even prior to infection. Taken together, our findings suggest that the composition of the microbiome may be a useful predictor of tuberculosis progression in infected individuals either directly because of the microbiome’s direct influence on host resistance or indirectly because of its association with other host factors that have this influence. This calls for exploration of the potential of the microbiota composition as a predictive biomarker through carefully designed prospective studies.


2014 ◽  
Vol 10 (9) ◽  
pp. e1004394 ◽  
Author(s):  
Neelima Sukumar ◽  
Shumin Tan ◽  
Bree B. Aldridge ◽  
David G. Russell

Hepatology ◽  
1992 ◽  
Vol 15 (5) ◽  
pp. 782-794 ◽  
Author(s):  
Manfred J. Müller ◽  
Hans U. Lautz ◽  
Birgit Plogmann ◽  
Mechthild Bürger ◽  
Jürgen Körber ◽  
...  

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