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1.
Elife ; 102021 12 10.
Article in English | MEDLINE | ID: mdl-34889185

ABSTRACT

Resistance mutations against one drug can elicit collateral sensitivity against other drugs. Multi-drug treatments exploiting such trade-offs can help slow down the evolution of resistance. However, if mutations with diverse collateral effects are available, a treated population may evolve either collateral sensitivity or collateral resistance. How to design treatments robust to such uncertainty is unclear. We show that many resistance mutations in Escherichia coli against various antibiotics indeed have diverse collateral effects. We propose to characterize such diversity with a joint distribution of fitness effects (JDFE) and develop a theory for describing and predicting collateral evolution based on simple statistics of the JDFE. We show how to robustly rank drug pairs to minimize the risk of collateral resistance and how to estimate JDFEs. In addition to practical applications, these results have implications for our understanding of evolution in variable environments.


Drugs known as antibiotics are the main treatment for most serious infections caused by bacteria. However, many bacteria are acquiring genetic mutations that make them resistant to the effects of one or more types of antibiotics, making them harder to eliminate. One way to tackle drug-resistant bacteria is to develop new types of antibiotics; however, in recent years, the rate at which new antibiotics have become available has been dwindling. Using two or more existing drugs, one after another, can also be an effective way to eliminate resistant bacteria. The success of any such 'multi-drug' treatment lies in being able to predict whether mutations that make the bacteria resistant to one drug simultaneously make it sensitive to another, a phenomenon known as collateral sensitivity. Different resistance mutations may have different collateral effects: some may increase the bacteria's sensitivity to the second drug, while others might make the bacteria more resistant. However, it is currently unclear how to design robust multi-drug treatments that take this diversity of collateral effects into account. Here, Ardell and Kryazhimskiy used a concept called JDFE (short for the joint distribution of fitness effects) to describe the diversity of collateral effects in a population of bacteria exposed to a single drug. This information was then used to mathematically model how collateral effects evolved in the population over time. Ardell and Kryazhimskiy showed that this approach can predict how likely a population is to become collaterally sensitive or collaterally resistant to a second antibiotic. Drug pairs can then be ranked according to the risk of collateral resistance emerging, so long as information on the variety of resistance mutations available to the bacteria are included in the model. Each year, more than 700,000 people die from infections caused by bacteria that are resistant to one or more antibiotics. The findings of Ardell and Kryazhimskiy may eventually help clinicians design multi-drug treatments that effectively eliminate bacterial infections and help to prevent more bacteria from evolving resistance to antibiotics. However, to achieve this goal, more research is needed to fully understand the range collateral effects caused by resistance mutations.


Subject(s)
Anti-Bacterial Agents/pharmacology , Drug Resistance, Bacterial/genetics , Escherichia coli/genetics , Genetic Fitness , Genetic Variation , Escherichia coli/drug effects
2.
Am J Physiol Heart Circ Physiol ; 317(5): H1134-H1141, 2019 11 01.
Article in English | MEDLINE | ID: mdl-31538809

ABSTRACT

Aberrant afferent signaling drives adverse remodeling of the cardiac nervous system in ischemic heart disease. The study objective was to determine whether thoracic spinal dorsal column stimulation (SCS) modulates cardiac afferent sensory transduction of the ischemic ventricle. In anesthetized canines (n = 16), extracellular activity generated by 62 dorsal root ganglia (DRG) soma (T1-T3), with verified myocardial ischemic (MI) sensitivity, were evaluated with and without 20-min preemptive SCS (T1-T3 spinal level; 50 Hz, 90% motor threshold). Transient MI was induced by 1-min coronary artery occlusion (CAO) of the left anterior descending (LAD) or circumflex (LCX) artery, randomized as to sequence. LAD and LCX CAO activated cardiac-related DRG neurons (LAD: 0.15 ± 0.04-1.05 ± 0.20 Hz, P < 0.00002; LCX: 0.08 ± 0.02-1.90 ± 0.45 Hz, P < 0.0003). SCS decreased basal neuronal activity of neurons that responded to LAD (0.15 ± 0.04 to 0.02 ± 0.01 Hz, P < 0.006) and LCX (0.08 ± 0.02 to 0.02 ± 0.01 Hz, P < 0.003). SCS suppressed responsiveness to transient MI (LAD: 1.05 ± 0.20-0.03 ± 0.01 Hz; P < 0.0001; LCX: 1.90 ± 0.45-0.03 ± 0.01 Hz; P < 0.001). Suprathreshold SCS (1 Hz) did not activate DRG neurons antidromically (n = 10 animals). Ventricular fibrillation (VF) was associated with a rapid increase in DRG activity to a maximum of 4.39 ± 1.07 Hz at 20 s after VF induction and a return to 90% of baseline within 10 s thereafter. SCS obtunds the capacity of DRG ventricular neurites to transduce the ischemic myocardium to second-order spinal neurons, a mechanism that would blunt reflex sympathoexcitation to myocardial ischemic stress, thereby contributing to its capacity to cardioprotect.NEW & NOTEWORTHY Aberrant afferent signaling drives adverse remodeling of the cardiac nervous system in ischemic heart disease. This study determined that thoracic spinal column stimulation (SCS) obtunds the capacity of dorsal root ganglia ventricular afferent neurons to transduce the ischemic myocardium to second-order spinal neurons, a mechanism that would blunt reflex sympathoexcitation to myocardial ischemic stress. This modulation does not reflect antidromic actions of SCS but likely reflects efferent-mediated changes at the myocyte-sensory neurite interface.


Subject(s)
Ganglia, Spinal/physiopathology , Heart Ventricles/innervation , Myocardial Infarction/therapy , Reflex , Sensory Receptor Cells , Spinal Cord Stimulation , Action Potentials , Animals , Disease Models, Animal , Dogs , Female , Male , Myocardial Infarction/physiopathology , Ventricular Fibrillation/physiopathology , Ventricular Fibrillation/prevention & control
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