Environment-independent distribution of mutational effects emerges from microscopic epistasis.

Predicting how new mutations alter phenotypes is difficult because mutational effects vary across genotypes and environments. Recently discovered global epistasis, where the fitness effects of mutations scale with the fitness of the background genotype, can improve predictions, but how the environment modulates this scaling is unknown. We measured the fitness effects of ~100 insertion mutations in 42 strains of Saccharomyces cerevisiae in six laboratory environments and found that the global-epistasis scaling is nearly invariant across environments. Instead, the environment tunes one global parameter, the background fitness at which most mutations switch sign. As a consequence, the distribution of mutational effects is remarkably predictable across genotypes and environments. Our results suggest that the effective dimensionality of genotype-to-phenotype maps across environments is surprisingly low.

The population genetics of collateral resistance and sensitivity.

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.

Thoracic spinal cord neuromodulation obtunds dorsal root ganglion afferent neuronal transduction of the ischemic ventricle.

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.

Optic Nerve Sheath Diameter for Preterm Infants: A Pilot Study.

OBJECTIVE: In preterm infants, early diagnosis and management of a raised intracranial pressure (ICP) may be important to improve neurodevelopmental outcomes. While invasive ICP monitoring is not recommended, ultrasonography of the optic nerve sheath diameter (ONSD) could provide a noninvasive alternative to evaluate ICP. The objective of this pilot study was to document ranges of ONSD in preterm infants. METHODS: This prospective cohort pilot evaluated preterm infants who were admitted to the neonatal intensive care unit without suspected raised ICP. Three images per eye were obtained from a 20-5 MHz linear array ultrasound transducer placed on the patient's superior eyelid. The OSND was measured 3 mm behind the globe. A second ultrasonographer duplicated half of the scans. Multiple linear regression analysis was conducted for both right and left ONSD with corrected gestational age, weight, and head circumference as predictors. Lin's concordance assessed interrater reliability. RESULTS: In 12 preterm infants 114 scans were performed on both eyes. The median age was 33 weeks (corrected gestational age) with a range of 29-36 weeks. Corrected gestational age was the strongest predictor for ONSD, and preliminary measurements at each gestational age were established. Interrater reliability demonstrated substantial agreement (Qc = 0.97). CONCLUSION: In preterm infants, ONSD strongly correlates with corrected gestational age. These data should be validated with other imaging modalities before abnormal ranges can be considered.