The Role of Fatty Acid Metabolism in Drug Tolerance of Mycobacterium tuberculosis

Understanding the mechanisms underlying M. tuberculosis adaptive strategies to achieve drug tolerance is crucial for the identification of new targets and the development of new drugs. Here, we show that acetate medium triggers a drug-tolerant state in M. tuberculosis when challenged with antituberculosis (anti-TB) drugs.

Autophagy as a Mechanism for Adaptive Prediction-Mediated Emergence of Drug Resistance

Drug resistance is a major problem in treatment of microbial infections and cancers. There is growing evidence that a transient drug tolerant state may precede and potentiate the emergence of drug resistance. Therefore, understanding the mechanisms leading to tolerance is critical for combating drug resistance and for the development of effective therapeutic strategy. Through laboratory evolution of yeast, we recently demonstrated that adaptive prediction (AP), a strategy employed by organisms to anticipate and prepare for a future stressful environment, can emerge within 100 generations by linking the response triggered by a neutral cue (caffeine) to a mechanism of protection against a lethal agent (5-fluoroorotic acid, 5-FOA). Here, we demonstrate that mutations selected across multiple laboratory-evolved lines had linked the neutral cue response to core genes of autophagy. Across these evolved lines, conditional activation of autophagy through AP conferred tolerance, and potentiated subsequent selection of mutations in genes specific to overcoming the toxicity of 5-FOA. These results offer a new perspective on how extensive genome-wide genetic interactions of autophagy could have facilitated the emergence of AP over short evolutionary timescales to potentiate selection of 5-FOA resistance-conferring mutations.

New Inhibitors in the Ageing Population: A retrospective, observational, cohort study of new inhibitors in older people with haemophilia

Introduction: A second peak of inhibitors has been reported in patients with severe haemophilia A (HA) aged >50 years in the UK.1 The reason for this suggested breakdown of tolerance in the ageing population is unclear, as is the potential impact of regular exposure to the deficient factor by prophylaxis at higher age. No data on haemophilia B (HB) has ever been reported. Aim: The ADVANCE Working Group investigated the incidence of late-onset inhibitors and the use of prophylaxis in patients with HA and HB aged ≥40 years. Methods: A retrospective, observational, cohort, survey-based study of all patients aged ≥40 years with HA or HB treated at an ADVANCE HTC. Results: Information on 3,095 people aged ≥40 years with HA or HB was collected. Of the 2,562 patients with severe HA, the majority (73% across all age groups) received prophylaxis. In patients with severe HA, the inhibitor incidence per 1,000 treatment years was 2.37 (age 40–49), 1.25 (age 50–59) and 1.45 (age 60+). Overall, the inhibitor incidence was greatest in those with moderate HA (5.77 (age 40–49), 6.59 (age 50–59) and 4.69 (age 60+) and the majority of inhibitor cases were preceded by a potential immune system challenge. No inhibitors in patients with haemophilia B were reported. Conclusion: Our data do not identify a second peak of inhibitor development in older patients with haemophilia. Prophylaxis may be beneficial in older patients with severe, and possibly moderate HA, to retain a tolerant state at higher age.

Shooting yourself in the foot: How immune cells induce antibiotic tolerance in microbial pathogens

Antibiotic treatment failure of infection is common and frequently occurs in the absence of genetically encoded antibiotic resistance mechanisms. In such scenarios, the ability of bacteria to enter a phenotypic state that renders them tolerant to the killing activity of multiple antibiotic classes is thought to contribute to antibiotic failure. Phagocytic cells, which specialize in engulfing and destroying invading pathogens, may paradoxically contribute to antibiotic tolerance and treatment failure. Macrophages act as reservoirs for some pathogens and impede penetration of certain classes of antibiotics. In addition, increasing evidence suggests that subpopulations of bacteria can survive inside these cells and are coerced into an antibiotic-tolerant state by host cell activity. Uncovering the mechanisms that drive immune-mediated antibiotic tolerance may present novel strategies to improving antibiotic therapy.

A trade-off between stress resistance and tolerance underlies the adaptive response to hydrogen peroxide

In response to environmental stress, cellular defense strategies may be divided into two categories: those, as in homeostatic systems, that seek to maintain cell proliferation by degrading the stressor (i.e., resistance); and those that ensure cell survival (i.e. tolerance), even if this is often at the expense of cell proliferation. In this study, we have explored the genetic bases of the antagonism between resistance and tolerance during the response to hydrogen peroxide (H2O2) in budding yeast. We show that inactivation of protein kinase A (PKA) by H2O2 signaling induces an abrupt transition from normal homeostatic function to a stress-tolerant state by protecting the growth machinery, hence maximizing cellular fitness in a changing environment. This model system paves the way for developing antiproliferative strategies that target both resistance and tolerance mechanisms to prevent relapse.

Adaptive Tolerant State Estimation under Model Uncertainty in Power Systems

In this paper an adaptive tolerant estimator using singular value decomposition is proposed for a distribution network under model uncertainty in power systems. The adaptive tolerant estimator was designed with adjusted parameters and adjusted weights to overcome the limitations of model uncertainty. The estimator that reduces the measurement errors is adaptive to fast parameter changes in complicated environments. The singular value decomposition method was combined into the state estimator, which extended the over-determined cases to under-determined cases under model uncertainty. The performance of the tolerant estimator was compared with the conventional adaptive estimator, and the tolerant estimator showed accurate estimations against model uncertainty in complicated measurement environments.