Convergent Evolution of Antibiotic Tolerance in Patients with Persistent Methicillin-Resistant Staphylococcus aureus Bacteremia.

Severe infections caused by methicillin-resistant Staphylococcus aureus (MRSA) are often complicated by persistent bacteremia (PB) despite active antibiotic therapy. Antibiotic resistance rarely contributes to MRSA-PB, suggesting an important role for antibiotic tolerance pathways. To identify bacterial factors associated with PB, we sequenced the whole genomes of 206 MRSA isolates derived from 20 patients with PB and looked for genetic signatures of adaptive within-host evolution. We found that genes involved in the tricarboxylic acid cycle (citZ and odhA) and stringent response (rel) bore repeated, independent, protein-altering mutations across multiple infections, indicative of convergent evolution. Both pathways have been linked previously to antibiotic tolerance. Mutations in citZ were identified most frequently, and further study showed they caused antibiotic tolerance through the loss of citrate synthase activity. Isolates harboring mutant alleles (citZ, odhA, and rel) were sampled at a low frequency from each patient but were detected in 10 (50%) of the patients. These results suggest that subpopulations of antibiotic-tolerant mutants emerge commonly during MRSA-PB. Methicillin-resistant Staphylococcus aureus (MRSA) is a leading cause of hospital-acquired infection. In severe cases, bacteria invade the bloodstream and cause bacteremia, a condition associated with high mortality. We analyzed the genomes of serial MRSA isolates derived from patients with bacteremia that persisted through active antibiotic therapy and found a frequent evolution of pathways leading to antibiotic tolerance. Antibiotic tolerance is distinct from antibiotic resistance, and the role of tolerance in clinical failure of antibiotic therapy is defined poorly. Our results show genetic evidence that perturbation of specific metabolic pathways plays an important role in the ability of MRSA to evade antibiotics during severe infection.

Mitotic Block and Epigenetic Repression Underlie Neurodevelopmental Defects and Neurobehavioral Deficits in Congenital Heart Disease.

Poor neurodevelopment is often observed with congenital heart disease (CHD), especially with mutations in chromatin modifiers. Here analysis of mice with hypoplastic left heart syndrome (HLHS) arising from mutations in Sin3A associated chromatin modifier Sap130 , and adhesion protein Pcdha9, revealed neurodevelopmental and neurobehavioral deficits reminiscent of those in HLHS patients. Microcephaly was associated with impaired cortical neurogenesis, mitotic block, and increased apoptosis. Transcriptional profiling indicated dysregulated neurogenesis by REST, altered CREB signaling regulating memory and synaptic plasticity, and impaired neurovascular coupling modulating cerebral blood flow. Many neurodevelopmental/neurobehavioral disease pathways were recovered, including autism and cognitive impairment. These same pathways emerged from genome-wide DNA methylation and Sap130 chromatin immunoprecipitation sequencing analyses, suggesting epigenetic perturbation. Mice with Pcdha9 mutation or forebrain-specific Sap130 deletion without CHD showed learning/memory deficits and autism-like behavior. These novel findings provide mechanistic insights indicating the adverse neurodevelopment in HLHS may involve cell autonomous/nonautonomous defects and epigenetic dysregulation and suggest new avenues for therapy.

Clinical rel mutations in Staphylococcus aureus prime pathogen expansion under nutrient stress.

Persistent infection by Staphylococcus aureus has been linked to the bacterial stringent response (SR), a conserved stress response pathway regulated by the Rel protein. Rel synthesizes (p)ppGpp "alarmones" in response to amino acid starvation, which enables adaptation to stress by modulating bacterial growth and virulence. We previously identified five novel protein-altering mutations in rel that arose in patients with persistent methicillin-resistant S. aureus bacteremia. The mutations mapped to both the enzymatic and regulatory protein domains of Rel. Here, we set out to characterize the phenotype of these mutations to understand how they may have been selected in vivo. After introducing each mutation into S. aureus strain JE2, we analyzed growth, fitness, and antibiotic profiles. Despite being located in different protein domains, we found that all of the mutations converged on the same phenotype. Each shortened the time of lag phase growth and imparted a fitness advantage in nutritionally depleted conditions. Through quantification of intracellular (p)ppGpp, we link this phenotype to increased SR activation, specifically during the stationary phase of growth. In contrast to two previously identified clinical rel mutations, we find that our rel mutations do not cause antibiotic tolerance. Instead, our findings suggest that in vivo selection was due to an augmented SR that primes cells for growth in nutrient-poor conditions, which may be a strategy for evading host-imposed nutritional immunity. Importance Host and pathogen compete for available nutrition during infection. For bacteria, the stringent response (SR) regulator Rel responds to amino acid deprivation by signaling the cell to modulate its growth rate, metabolism, and virulence. In this report, we characterize five rel mutations that arose during cases of persistent methicillin-resistant Staphylococcus aureus bacteremia. We find that all of the mutations augmented SR signaling specifically under nutrient-poor conditions, enabling the cell to more readily grow and survive. Our findings reveal a strategy used by bacterial pathogens to evade the nutritional immunity imposed by host tissues during infection.

The Parameter-Fitness Landscape of lexA Autoregulation in Escherichia coli.

Feedback mechanisms are fundamental to the control of physiological responses. One important example in gene regulation, termed negative autoregulation (NAR), occurs when a transcription factor (TF) inhibits its own production through transcriptional repression. This enables more-rapid homeostatic control of gene expression. NAR circuits presumably evolve to limit the fitness costs of gratuitous gene expression. The key biochemical reactions of NAR can be parameterized using a mathematical model of promoter activity; however, this model of NAR has been studied mostly in the context of synthetic NAR circuits that are disconnected from the target genes of the TFs. Thus, it remains unclear how constrained NAR parameters are in a native circuit context, where the TF target genes can have fitness effects on the cell. To quantify these constraints, we created a panel of Escherichia coli strains with different lexA-NAR circuit parameters and analyzed the effect on SOS response function and bacterial fitness. Using a mathematical model for NAR, these experimental data were used to calculate NAR parameter values and derive a parameter-fitness landscape. Without feedback, survival of DNA damage was decreased due to high LexA concentrations and slower SOS "turn-on" kinetics. However, we show that, even in the absence of DNA damage, the lexA promoter is strong enough that, without feedback, high levels of lexA expression result in a fitness cost to the cell. Conversely, hyperfeedback can mimic lexA deletion, which is also costly. This work elucidates the lexA-NAR parameter values capable of balancing the cell's requirement for rapid SOS response activation with limiting its toxicity.IMPORTANCE Feedback mechanisms are critical to control physiological responses. In gene regulation, one important example, termed negative autoregulation (NAR), occurs when a transcription factor (TF) inhibits its own production. NAR is common across the tree of life, enabling rapid homeostatic control of gene expression. NAR behavior can be described in accordance with its core biochemical parameters, but how constrained these parameters are by evolution is unclear. Here, we describe a model genetic network controlled by an NAR circuit within the bacterium Escherichia coli and elucidate these constraints by experimentally changing a key parameter and measuring its effect on circuit response and fitness. This analysis yielded a parameter-fitness landscape representing the genetic network, providing a window into what gene-environment conditions favor evolution of this regulatory strategy.