Biology subjects

Amicone, M.

Publications and source records attributed to Amicone, M..

4 recordsLinked to original sources

bioRxiv2026

A competition-protection balance explains the evolution of resistance within simple microbial communities

Stressful environments can pose a threat to microbial populations, but resistant individuals can emerge and avoid extinction. Adaptation to stress is classically studied in isolated microbial species, ignoring ecological interactions, a key component of natural ecosystems. A growing body of experimental work has shown that community context can affect resistance evolution due to a large variety of mechanisms. Here we set out to identify the minimal components needed to predict the likelihood of acquiring resistance in a focal species embedded within a simple community. To achieve this, we developed a mathematical model based on evolutionary rescue theory and validated it with two experimental systems: Escherichia coli evolving on exposure to the antibiotic nitrofurantoin alone or with one of 14 bacterial isolates from urinary tract infections, and Microbacterium liquefaciens evolving in ampicillin alone or with ampicillin-degrading Comamonas testosteroni. One key factor that emerged from our analyses - the relative strength of competition versus protection - could explain whether a focal species is more or less likely to evolve resistance in the presence of a partner species. While competition always hinders the emergence of resistance, protection can rescue the focal species in two ways: (i) ecological rescue, when the partner species completely removes the antibiotic and favors the survival of the susceptible population, or (ii) evolutionary rescue, when the partner only lowers antibiotic concentrations and favors the emergence of resistant variants, a previously overlooked evolutionary consequence of detoxification. Overall, by integrating theory and experiments, we propose a framework that clarifies how ecological interactions favor or hinder the evolution of resistance to antibiotics or potentially other stressors. SignificanceBacteria can rapidly adapt to resist stressors, such as antibiotics. While resistance evolution in single populations or species is well understood, it remains unclear how ecological interactions with other species influence this process. We develop a mathematical framework to predict what interactions should favor resistance evolution and validate it with two sets of experiments where bacteria adapt to antibiotics in small communities. Our work demonstrates that interactions with other species shape the probability of evolving resistance in a predictable way, determined by the balance between competition and protection against the stressor. By identifying the key factors that drive these dynamics, our work helps explain how bacteria adapt to environmental challenges within species-rich ecosystems.

microbiology↗

bioRxiv2021

Mutation rate of SARS-CoV-2 and emergence of mutators during experimental evolution

Background and objectivesTo understand how organisms evolve, it is fundamental to study how mutations emerge and establish. Here, we estimated the rate of mutation accumulation of SARS-CoV-2 in vitro and investigated the repeatability of its evolution when facing a new cell type but no immune or drug pressures. MethodologyWe performed experimental evolution with two strains of SARS-CoV-2, one carrying the originally described spike protein (CoV-2-D) and another carrying the D614G mutation that has spread worldwide (CoV-2-G). After 15 passages in Vero cells and whole genome sequencing, we characterized the spectrum and rate of the emerging mutations and looked for evidences of selection across the genomes of both strains. ResultsFrom the mutations accumulated, and excluding the genes with signals of selection, we estimate a spontaneous mutation rate of 1.25x10-6 nt-1 per infection cycle for both lineages of SARS-CoV-2. We further show that mutation accumulation is heterogeneous along the genome, with the spike gene accumulating mutations at rate five-fold higher than the genomic average. We also observe the emergence of mutators in the CoV-2-G background, likely linked to mutations in the RNA-dependent RNA polymerase and/or in the error-correcting exonuclease protein. Conclusions and implicationsThese results provide valuable information on how spontaneous mutations emerge in SARS-CoV-2 and on how selection can shape its genome towards adaptation to new environments. Lay summaryMutation is the ultimate source of variation. We estimated how the SARS-COV-2 virus--cause of the COVID-19 pandemic--mutates. Upon infecting cells, its genome can change at a rate of 0.04 per replication. We also find that this rate can change and that its spike protein can adapt, even within few replications.

evolutionary biology↗

bioRxiv2020

Molecular signatures of resource competition: clonal interference drives the emergence of ecotypes

Microbial ecosystems harbor an astonishing diversity that can persist for long times. To understand how such diversity is structured and maintained, ecological and evolutionary processes need to be integrated at similar timescales. Here, we study a model of resource competition that allows for evolution via de novo mutation, and focus on rapidly adapting asexual populations with large mutational inputs, as typical of many bacteria species. We characterize the adaptation and diversification of an initially maladapted population and show how the eco-evolutionary dynamics are shaped by the interaction between simultaneously emerging lineages - clonal interference. We find that in large populations, more intense clonal interference fosters diversification under sympatry, increasing the probability that phenotypically and genetically distinct clusters stably coexist. In smaller populations, the accumulation of deleterious and compensatory mutations can push further the diversification process and kick-start speciation. Our findings have implications beyond microbial populations, providing novel insights about the interplay between ecology and evolution in clonal populations.

evolutionary biology↗

bioRxiv2019

Dysbiosis personalizes fitness effect of antibiotic resistance in the mammalian gut

The fitness cost of antibiotic resistance in the absence of antibiotics is crucial to the success of suspending antibiotics as a strategy to lower resistance. Here we show that after antibiotic treatment the cost of resistance within the complex ecosystem of the mammalian gut is personalized. Using mice as an in vivo model, we find that the fitness effect of the same resistant mutation can be deleterious in a host, but neutral or even beneficial in other hosts. Such antagonistic pleiotropy is shaped by the microbiota, as in germ-free mice resistance is consistently costly across all hosts. An eco-evolutionary model of competition for resources identifies a general mechanism underlying between host variation and predicts that the dynamics of compensatory evolution of resistant bacteria should be host specific, a prediction that was supported by experimental evolution in vivo. The microbiome of each human is close to unique and our results suggest that the short-term costs of resistance and its long-term within-host evolution will also be highly personalized, a finding that may contribute to the observed variable outcome of control therapies.\n\nOne Sentence SummaryPersonalized Fitness of Resistance Mutations.

evolutionary biology↗