scholarly journals Polyclonal pathogen populations accelerate the evolution of antibiotic resistance in patients

2021 ◽  
Author(s):  
Julio Diaz Caballero ◽  
Rachel M. Wheatley ◽  
Natalia Kapel ◽  
Carla López-Causapé ◽  
Thomas Van der Schalk ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
De Novo ◽  
Opportunistic Pathogen ◽  
Response To Treatment ◽  
Resistance Mutations ◽  
Trade Offs ◽  
Resistant Strains ◽  
Selection For ◽  
Pathogen Populations ◽  
Emergence Of Resistance

AbstractAntibiotic resistance poses a global health threat, but the within-host drivers of resistance remain poorly understood. Pathogen populations are often assumed to be clonal within hosts, and resistance is thought to emerge due to selection for de novo variants. Here we show that pulmonary populations of the opportunistic pathogen P. aeruginosa are often polyclonal. Crucially, resistance evolves rapidly in patients colonized by polyclonal populations through selection for pre-existing resistant strains. In contrast, resistance evolves sporadically in patients colonized by monoclonal populations due to selection for novel resistance mutations. However, strong trade-offs between resistance and fitness occur in polyclonal populations that can drive the loss of resistant strains. In summary, we show that the within-host diversity of pathogen populations plays a key role in shaping the emergence of resistance in response to treatment.One sentence summaryAntibiotic resistance evolves quickly in patients colonized by polyclonal pathogen populations.

scholarly journals Emergence of Resistance Mutations in Salmonella enterica Serovar Typhi Against Fluoroquinolones

2017 ◽  
Vol 4 (4) ◽  
Author(s):  
Takashi Matono ◽  
Masatomo Morita ◽  
Koji Yahara ◽  
Ken-ichi Lee ◽  
Hidemasa Izumiya ◽  
...  
Keyword(s):  
Salmonella Enterica ◽  
Evolutionary Process ◽  
Resistance Mechanisms ◽  
Single Mutation ◽  
Nucleotide Polymorphisms ◽  
Resistance Mutations ◽  
Single Nucleotide ◽  
Salmonella Enterica Serovar Typhi ◽  
Resistant Strains ◽  
Emergence Of Resistance

Abstract Background Little is known about the evolutionary process and emergence time of resistance mutations to fluoroquinolone in Salmonella enterica serovar Typhi. Methods We analyzed S. Typhi isolates collected from returned travelers between 2001 and 2016. Based on ciprofloxacin susceptibility, isolates were categorized as highly resistant (minimum inhibitory concentration [MIC] ≥ 4 μg/mL [CIPHR]), resistant (MIC = 1–2 μg/mL [CIPR]), intermediate susceptible (MIC = 0.12–0.5 μg/mL [CIPI]), and susceptible (MIC ≤ 0.06 μg/mL [CIPS]). Results A total of 107 isolates (33 CIPHR, 14 CIPR, 30 CIPI, and 30 CIPS) were analyzed by whole-genome sequencing; 2461 single nucleotide polymorphisms (SNPs) were identified. CIPS had no mutations in the gyrA or parC genes, while each CIPI had 1 of 3 single mutations in gyrA (encoding Ser83Phe [63.3%], Ser83Tyr [33.3%], or Asp87Asn [3.3%]). CIPHR had the same 3 mutations: 2 SNPs in gyrA (encoding Ser83Phe and Asp87Asn) and a third in parC (encoding Ser80Ile). CIPHR shared a common ancestor with CIPR and CIPI isolates harboring a single mutation in gyrA encoding Ser83Phe, suggesting that CIPHR emerged 16 to 23 years ago. Conclusions Three SNPs—2 in gyrA and 1 in parC—are present in S. Typhi strains highly resistant to fluoroquinolone, which were found to have evolved in 1993–2000, approximately 10 years after the beginning of the ciprofloxacin era. Highly resistant strains with survival advantages arose from strains harboring a single mutation in gyrA encoding Ser83Phe. Judicious use of fluoroquinolones is warranted to prevent acceleration of such resistance mechanisms in the future.

scholarly journals Stochastic bacterial population dynamics restrict the establishment of antibiotic resistance from single cells

2020 ◽  
Vol 117 (32) ◽  
pp. 19455-19464 ◽  
Author(s):  
Helen K. Alexander ◽  
R. Craig MacLean
Keyword(s):  
De Novo ◽  
Single Cells ◽  
Treatment Strategies ◽  
Bacterial Populations ◽  
Resistance Plasmids ◽  
Evolution Of Resistance ◽  
Resistant Strains ◽  
Low Probability ◽  
Emergence Of Resistance ◽  
Resistant Cells

A better understanding of how antibiotic exposure impacts the evolution of resistance in bacterial populations is crucial for designing more sustainable treatment strategies. The conventional approach to this question is to measure the range of concentrations over which resistant strain(s) are selectively favored over a sensitive strain. Here, we instead investigate how antibiotic concentration impacts the initial establishment of resistance from single cells, mimicking the clonal expansion of a resistant lineage following mutation or horizontal gene transfer. Using twoPseudomonas aeruginosastrains carrying resistance plasmids, we show that single resistant cells have <5% probability of detectable outgrowth at antibiotic concentrations as low as one-eighth of the resistant strain’s minimum inhibitory concentration (MIC). This low probability of establishment is due to detrimental effects of antibiotics on resistant cells, coupled with the inherently stochastic nature of cell division and death on the single-cell level, which leads to loss of many nascent resistant lineages. Our findings suggest that moderate doses of antibiotics, well below the MIC of resistant strains, may effectively restrict de novo emergence of resistance even though they cannot clear already-large resistant populations.

scholarly journals Generation and initial characterization of a collection of spontaneous Streptomyces albus J1074 mutants resistant to rifampicin

2020 ◽  
Vol 27 ◽  
pp. 139-143
Author(s):  
B. O. Ostash ◽  
Yu. Misaki ◽  
B. S. Dolya ◽  
Ya. I. Kharaton ◽  
T. Busche ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Wide Spectrum ◽  
Gene Clusters ◽  
Antibiotic Activity ◽  
Missense Mutations ◽  
Resistance Mutations ◽  
Resistance Level ◽  
Streptomyces Albus ◽  
Selection For ◽  
Streptomyces Albus J1074

Aim. Streptomyces albus J1074 is one of the most popular streptomycete chassis for heterologous expression of natural product (NP) biosynthetic gene clusters (BGCs). There is keen interest in further improvement of the strain to provide increased yields of corresponding NPs. Introduction of certain types of antibiotic resistance mutations is a proven way to improve Streptomyces strains. For example, selection for increased resistance to rifampicin is known to lead to increased antibiotic activity. Here we used available lineages of antibiotic-resistant mutants of S. albus to raise rifampicin-resistant variants (Rifr) and to study their properties. Methods. Microbiological and molecular genetic approaches were combined to generate Rifr mutants and to study their properties. Results. By plating S. albus onto GYM agar supplemented with 10 mcg/mL of rifampicin, we isolated 85 stable Rifr colonies, whose resistance level was within 10-200 mcg/mL range. Sequencing revealed wide spectrum of missense mutations within rpoB gene. Bioassays demonstrated dramatically increased endogenous antibiotic activity of certain Rifr mutants. Conclusions. Selection for rifampicin resistance is a viable way to increase the yields of NPs in S. albus. Keywords: Streptomyces albus J1074, antibiotic resistance, rifampicin.

scholarly journals Pleiotropy complicates a trade-off between phage resistance and antibiotic resistance

2020 ◽  
Vol 117 (21) ◽  
pp. 11207-11216 ◽  
Author(s):  
Alita R. Burmeister ◽  
Abigail Fortier ◽  
Carli Roush ◽  
Adam J. Lessing ◽  
Rose G. Bender ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Molecular Mechanisms ◽  
Efflux Pump ◽  
Resistance Mechanisms ◽  
Phage Resistance ◽  
Resistance Mutations ◽  
Trade Off ◽  
Trade Offs ◽  
Evolutionary Context ◽  
Structural Barrier

Bacteria frequently encounter selection by both antibiotics and lytic bacteriophages. However, the evolutionary interactions between antibiotics and phages remain unclear, in particular, whether and when phages can drive evolutionary trade-offs with antibiotic resistance. Here, we describeEscherichia coliphage U136B, showing it relies on two host factors involved in different antibiotic resistance mechanisms: 1) the efflux pump protein TolC and 2) the structural barrier molecule lipopolysaccharide (LPS). Since TolC and LPS contribute to antibiotic resistance, phage U136B should select for their loss or modification, thereby driving a trade-off between phage resistance and either of the antibiotic resistance mechanisms. To test this hypothesis, we used fluctuation experiments and experimental evolution to obtain phage-resistant mutants. Using these mutants, we compared the accessibility of specific mutations (revealed in the fluctuation experiments) to their actual success during ecological competition and coevolution (revealed in the evolution experiments). BothtolCand LPS-related mutants arise readily during fluctuation assays, withtolCmutations becoming more common during the evolution experiments. In support of the trade-off hypothesis, phage resistance viatolCmutations occurs with a corresponding reduction in antibiotic resistance in many cases. However, contrary to the hypothesis, some phage resistance mutations pleiotropically confer increased antibiotic resistance. We discuss the molecular mechanisms underlying this surprising pleiotropic result, consideration for applied phage biology, and the importance of ecology in evolution of phage resistance. We envision that phages may be useful for the reversal of antibiotic resistance, but such applications will need to account for unexpected pleiotropy and evolutionary context.

scholarly journals Epistasis between antibiotic resistance mutations and genetic background shape the fitness effect of resistance across species of Pseudomonas

2016 ◽  
Vol 283 (1830) ◽  
pp. 20160151 ◽  
Author(s):  
T. Vogwill ◽  
M. Kojadinovic ◽  
R. C. MacLean
Keyword(s):  
Antibiotic Resistance ◽  
Resistance Mutations ◽  
Bacterial Strains ◽  
Fitness Effect ◽  
Epistatic Interactions ◽  
Fitness Effects ◽  
Cost Of Resistance ◽  
Pathogen Populations ◽  
The Cost ◽  
Antibiotic Resistance Mutations

Antibiotic resistance often evolves by mutations at conserved sites in essential genes, resulting in parallel molecular evolution between divergent bacterial strains and species. Whether these resistance mutations are having parallel effects on fitness across bacterial taxa, however, is unclear. This is an important point to address, because the fitness effects of resistance mutations play a key role in the spread and maintenance of resistance in pathogen populations. We address this idea by measuring the fitness effect of a collection of rifampicin resistance mutations in the β subunit of RNA polymerase ( rpoB ) across eight strains that span the diversity of the genus Pseudomonas . We find that almost 50% of rpoB mutations have background-dependent fitness costs, demonstrating that epistatic interactions between rpoB and the rest of the genome are common. Moreover, epistasis is typically strong, and it is the dominant genetic determinant of the cost of resistance mutations. To investigate the functional basis of epistasis, and because rpoB plays a central role in transcription, we measured the effects of common rpoB mutations on transcriptional efficiency across three strains of Pseudomonas . Transcriptional efficiency correlates strongly to fitness across strains, and epistasis arises because individual rpoB mutations have differential effects on transcriptional efficiency in different genetic backgrounds.

scholarly journals Antibiotic Resistance Increases Evolvability and Maximizes Opportunities Across Fitness Landscapes

2019 ◽  
Author(s):  
Fabrizio Spagnolo ◽  
Daniel E. Dykhuizen
Keyword(s):  
Public Health ◽  
Antibiotic Resistance ◽  
Public Health Problem ◽  
Fitness Landscapes ◽  
Resistant Bacteria ◽  
Major Question ◽  
Antibiotic Resistant ◽  
Resistant Strains ◽  
Compensatory Mutations ◽  
Selection For

AbstractAntibiotic resistance continues to grow as a public health problem. One of the reasons for this continued growth is that resistance to antibiotics is strongly selected for in the presence of antibiotics and weakly selected against after their removal. This is frequently thought to be due to the effects of compensatory mutations. However, compensatory mutations are often not found in clinically relevant strains of antibiotic resistant pathogens. Here, we conduct experiments in vitro that highlight the role that fine scale differences in environment play in the maintenance of populations after selection for resistance. We show that differences in the mode of growth, dictated by environmental factors, are capable of reliably changing the force and direction of selection. Our results show that antibiotic resistance can increase evolvability in environments if conditions for selection exist, selecting differentially for newly arising variation and moving populations to previously unavailable adaptive peaks.SignificanceAntibiotic resistant bacteria are a large and growing problem for public health. A major question has been why antibiotic resistant strains do not disappear when they must compete with higher fitness drug sensitive strains. Here we show that selection for antibiotic resistant strains is particularly sensitive to differences in environmental conditions and that these differences help to define the fitness landscapes upon which these populations adapt. The result is an increase in evolvability, with many adaptive peaks that drug resistant populations can explore through natural selection, making predictions of evolution difficult and selection against resistant strains improbable.

scholarly journals Stochastic bacterial population dynamics prevent the emergence of antibiotic resistance from single cells

2018 ◽  
Author(s):  
Helen K. Alexander ◽  
R. Craig MacLean
Keyword(s):  
Antibiotic Resistance ◽  
Single Cell ◽  
Bacterial Population ◽  
De Novo ◽  
Single Cells ◽  
Mutant Selection ◽  
Selection Window ◽  
Low Probability ◽  
Emergence Of Resistance ◽  
Resistant Cells

AbstractA better understanding of how antibiotic exposure impacts the evolution of resistance is crucial for designing more sustainable treatment strategies. The conventional approach to relating antibiotic dose to resistance evolution within a bacterial population is to measure the range of concentrations over which resistant strain(s) are selectively favoured over a sensitive strain – the “mutant selection window”. Here, we instead investigate how antibiotic concentration impacts the initial establishment of resistance from single cells, mimicking the clonal expansion of a resistant lineage following mutation or horizontal gene transfer. Using two Pseudomonas aeruginosa strains carrying distinct resistance plasmids, we show that single resistant cells have <5% probability of outgrowth at antibiotic concentrations as low as 1/8th of the resistant strain’s minimum inhibitory concentration. This low probability of establishment is due to detrimental effects of antibiotics on resistant cells, coupled with the inherently stochastic nature of cell division and death on the single-cell level, which leads to loss of many nascent resistant lineages. Our findings suggest that moderate doses of antibiotics, within the traditional mutant selection window, may be more effective at preventing de novo emergence of resistance than predicted by deterministic approaches.Significance statementThe emergence of antibiotic resistance poses a critical threat to the efficacy of antibiotic treatments. A resistant bacterial population must originally arise from a single cell that mutates or acquires a resistance gene. This single cell may, by chance, fail to successfully reproduce before it dies, leading to loss of the nascent resistant lineage. Here we show that antibiotic concentrations that selectively favour resistance are nonetheless sufficient to reduce the chance of outgrowth from a single cell to a very low probability. Our findings suggest that lower antibiotic concentrations than previously thought may be sufficient to prevent, with high probability, emergence of resistance from single cells.

scholarly journals Genetic determinants of antibiotic resistance and the evolution of trade-offs during adaptation in a single patient

2021 ◽  
Author(s):  
Robert J Woods ◽  
Camilo Barbosa ◽  
Laura Koepping ◽  
Juan A. Raygoza Garay ◽  
Michael Mwangi ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
De Novo ◽  
Laboratory Data ◽  
Genetic Material ◽  
Treatment Strategies ◽  
Single Patient ◽  
De Novo Mutations ◽  
Collateral Sensitivity ◽  
Trade Offs ◽  
Evolutionary Trajectories

The processes by which pathogens evolve within single hosts dictate the efficacy of treatment strategies designed to slow antibiotic resistance evolution and influence the population-wide resistance levels. The aim of this study is to describe the underlying genetic and phenotypic changes leading to antibiotic resistance within a single patient who died as resistance evolved to available antibiotics. We assess whether robust patterns of collateral sensitivity and response to combinations exist that might have been leveraged to improve therapy. Whole-genome sequencing was completed for nine isolates taken from this patient over 279 days of chronic infection with Enterobacter hormaechei, along with systematic measurements of changes in resistance against five of the most relevant drugs considered for treatment. The entirety of the genetic change is consistent with de novo mutations and plasmid loss events, without the acquisition of foreign genetic material via horizontal gene transfer. The isolates formed three genetically distinct lineages, with early evolutionary trajectories being supplanted by previously unobserved multi-step evolutionary trajectories. Importantly, no single isolate evolved resistance to all of the antibiotics considered for treatment against E. hormaechei (i.e., none was pan-resistant). Patterns of collateral sensitivity and response to combination therapy revealed contrasting patterns across this diversifying population. Translating antibiotic resistance management strategies from theoretical and laboratory data to clinical situations, such as this, may require managing diverse populations with unpredictable resistance trajectories.

Sign in / Sign up

Export Citation Format

Share Document