Effects of genotype on rates of substitution during experimental evolution

Substrate cross-feeding affects the speed and trajectory of molecular evolution within a synthetic microbial assemblage

Background

Substrate cross-feeding occurs when one organism partially consumes a primary substrate into one or more metabolites while other organisms then consume the metabolites. While pervasive within microbial communities, our knowledge about the effects of substrate cross-feeding on microbial evolution remains limited. To address this knowledge gap, we experimentally evolved isogenic nitrite (NO₂⁻) cross-feeding microbial strains together for 700 generations, identified genetic changes that were acquired over the evolution experiment, and compared the results with an isogenic completely denitrifying strain that was evolved alone for 700 generations. We further investigated how the magnitude of interdependence between the nitrite cross-feeding strains affects the main outcomes. Our main objective was to quantify how substrate cross-feeding and the magnitude of interdependence affect the speed and trajectory of molecular evolution.

Results

We found that each nitrite (NO₂⁻) cross-feeding strain acquired fewer genetic changes than did the completely denitrifying strain. In contrast, pairs of nitrite cross-feeding strains together acquired more genetic changes than did the completely denitrifying strain. Moreover, nitrite cross-feeding promoted population diversification, as pairs of nitrite cross-feeding strains acquired a more varied set of genetic changes than did the completely denitrifying strain. These outcomes likely occurred because nitrite cross-feeding enabled the co-existence of two distinct microbial strains, thus increasing the amount of genetic variation for selection to act upon. Finally, the nitrite cross-feeding strains acquired different types of genetic changes than did the completely denitrifying strain, indicating that nitrite cross-feeding modulates the trajectory of molecular evolution.

Conclusions

Our results demonstrate that substrate cross-feeding can affect both the speed and trajectory of molecular evolution within microbial populations. Substrate cross-feeding can therefore have potentially important effects on the life histories of microorganisms.

Electronic supplementary material

The online version of this article (10.1186/s12862-019-1458-4) contains supplementary material, which is available to authorized users.

Fitness Tradeoffs of Antibiotic Resistance in Extraintestinal Pathogenic Escherichia coli

Evolutionary trade-offs occur when selection on one trait has detrimental effects on other traits. In pathogenic microbes, it has been hypothesized that antibiotic resistance trades off with fitness in the absence of antibiotic. Although studies of single resistance mutations support this hypothesis, it is unclear whether trade-offs are maintained over time, due to compensatory evolution and broader effects of genetic background. Here, we leverage natural variation in 39 extraintestinal clinical isolates of Escherichia coli to assess trade-offs between growth rates and resistance to fluoroquinolone and cephalosporin antibiotics. Whole-genome sequencing identifies a broad range of clinically relevant resistance determinants in these strains. We find evidence for a negative correlation between growth rate and antibiotic resistance, consistent with a persistent trade-off between resistance and growth. However, this relationship is sometimes weak and depends on the environment in which growth rates are measured. Using in vitro selection experiments, we find that compensatory evolution in one environment does not guarantee compensation in other environments. Thus, even in the face of compensatory evolution and other genetic background effects, resistance may be broadly costly, supporting the use of drug restriction protocols to limit the spread of resistance. Furthermore, our study demonstrates the power of using natural variation to study evolutionary trade-offs in microbes.

Effect of Population Size and Mutation Rate on the Evolution of RNA Sequences on an Adaptive Landscape Determined by RNA Folding

The dynamics of populations evolving on an adaptive landscape depends on multiple factors, including the structure of the landscape, the rate of mutations, and effective population size. Existing theoretical work often makes ad hoc and simplifying assumptions about landscape structure, whereas experimental work can vary important parameters only to a limited extent. We here overcome some of these limitations by simulating the adaptive evolution of RNA molecules, whose fitness is determined by the thermodynamics of RNA secondary structure folding. We study the influence of mutation rates and population sizes on final mean population fitness, on the substitution rates of mutations, and on population diversity. We show that evolutionary dynamics cannot be understood as a function of mutation rate µ, population size N, or population mutation rate Nµ alone. For example, at a given mutation rate, clonal interference prevents the fixation of beneficial mutations as population size increases, but larger populations still arrive at a higher mean fitness. In addition, at the highest population mutation rates we study, mean final fitness increases with population size, because small populations are driven to low fitness by the relatively higher incidence of mutations they experience. Our observations show that mutation rate and population size can interact in complex ways to influence the adaptive dynamics of a population on a biophysically motivated fitness landscape.

Time-Resolved Tracking of Mutations Reveals Diverse Allele Dynamics during Escherichia coli Antimicrobial Adaptive Evolution to Single Drugs and Drug Pairs

Understanding the evolutionary processes that lead to antibiotic resistance can help to achieve better treatment strategies. Yet, little is known about the dynamics of the resistance alleles during adaptation. Here, we use population sequencing to monitor genetic changes in putative resistance loci at several time-points during adaptive evolution experiments involving five different antibiotic conditions. We monitor the mutational spectra in lineages evolved to be resistant to single antibiotics [amikacin (AMK), chloramphenicol (CHL), and ciprofloxacin (CIP)], as well as antibiotic combinations (AMK + CHL and CHL + CIP). We find that lineages evolved to antibiotic combinations exhibit different resistance allele dynamics compared with those of single-drug evolved lineages, especially for a drug pair with reciprocal collateral sensitivity. During adaptation, we observed interfering, superimposing and fixation allele dynamics. To further understand the selective forces driving specific allele dynamics, a subset of mutations were introduced into the ancestral wild type enabling differentiation between clonal interference and negative epistasis.

Epistasis and the Evolution of Antimicrobial Resistance

The fitness effects of a mutation can depend, sometimes dramatically, on genetic background; this phenomenon is often referred to as “epistasis.” Epistasis can have important practical consequences in the context of antimicrobial resistance (AMR). For example, genetic background plays an important role in determining the costs of resistance, and hence in whether resistance will persist in the absence of antibiotic pressure. Furthermore, interactions between resistance mutations can have important implications for the evolution of multi-drug resistance. I argue that there is a need to better characterize the extent and nature of epistasis for mutations and horizontally transferred elements conferring AMR, particularly in clinical contexts. Furthermore, I suggest that epistasis should be an important consideration in attempts to slow or limit the evolution of AMR.

Epistatic interactions between ancestral genotype and beneficial mutations shape evolvability in Pseudomonas aeruginosa

The idea that interactions between mutations influence adaptation by driving populations to low and high fitness peaks on adaptive landscapes is deeply ingrained in evolutionary theory. Here, we investigate the impact of epistasis on evolvability by challenging populations of two Pseudomonas aeruginosa clones bearing different initial mutations (in rpoB conferring rifampicin resistance, and the type IV pili gene network) to adaptation to a medium containing l-serine as the sole carbon source. Despite being initially indistinguishable in fitness, populations founded by the two ancestral genotypes reached different fitness following 300 generations of evolution. Genome sequencing revealed that the difference could not be explained by acquiring mutations in different targets of selection; the majority of clones from both ancestors converged on one of the following two strategies: (1) acquiring mutations in either PA2449 (gcsR, an l-serine-metabolism RpoN enhancer binding protein) or (2) protease genes. Additionally, populations from both ancestors converged on loss-of-function mutations in the type IV pili gene network, either due to ancestral or acquired mutations. No compensatory or reversion mutations were observed in RNA polymerase (RNAP) genes, in spite of the large fitness costs typically associated with mutations in rpoB. Although current theory points to sign epistasis as the dominant constraint on evolvability, these results suggest that the role of magnitude epistasis in constraining evolvability may be underappreciated. The contribution of magnitude epistasis is likely to be greatest under the biologically relevant mutation supply rates that make back mutations probabilistically unlikely.

Clinical Isolates of Pseudomonas aeruginosa from Chronically Infected Cystic Fibrosis Patients Fail To Activate the Inflammasome during Both Stable Infection and Pulmonary Exacerbation

Immune recognition of pathogen-associated ligands leads to assembly and activation of inflammasomes, resulting in the secretion of inflammatory cytokines IL-1β and IL-18 and an inflammatory cell death called pyroptosis. Inflammasomes are important for protection against many pathogens, but their role during chronic infectious disease is poorly understood. Pseudomonas aeruginosa is an opportunistic pathogen that persists in the lungs of cystic fibrosis (CF) patients and may be responsible for the repeated episodes of pulmonary exacerbation characteristic of CF. P. aeruginosa is capable of inducing potent inflammasome activation during acute infection. We hypothesized that to persist within the host during chronic infection, P. aeruginosa must evade inflammasome activation, and pulmonary exacerbations may be the result of restoration of inflammasome activation. We therefore isolated P. aeruginosa from chronically infected CF patients during stable infection and exacerbation and evaluated the impact of these isolates on inflammasome activation in macrophages and neutrophils. P. aeruginosa isolates from CF patients failed to induce inflammasome activation, as measured by the secretion of IL-1β and IL-18 and by pyroptotic cell death, during both stable infection and exacerbation. Inflammasome evasion likely was due to reduced expression of inflammasome ligands and reduced motility and was not observed in environmental isolates or isolates from acute, non-CF infection. These results reveal a novel mechanism of pathogen adaptation by P. aeruginosa to avoid detection by inflammasomes in CF patients and indicate that P. aeruginosa-activated inflammasomes are not involved in CF pulmonary exacerbations.