Population bottlenecks strongly affect the evolutionary dynamics of antibiotic persistence

Abstract Bacterial persistence is a potential cause of antibiotic therapy failure. Antibiotic-tolerant persisters originate from phenotypic differentiation within a susceptible population, occurring with a frequency that can be altered by mutations. Recent studies have proven that persistence is a highly evolvable trait and, consequently, an important evolutionary strategy of bacterial populations to adapt to high-dose antibiotic therapy. Yet, the factors that govern the evolutionary dynamics of persistence are currently poorly understood. Theoretical studies predict far-reaching effects of bottlenecking on the evolutionary adaption of bacterial populations, but these effects have never been investigated in the context of persistence. Bottlenecking events are frequently encountered by infecting pathogens during host-to-host transmission and antibiotic treatment. In this study, we used a combination of experimental evolution and barcoded knockout libraries to examine how population bottlenecking affects the evolutionary dynamics of persistence. In accordance with existing hypotheses, small bottlenecks were found to restrict the adaptive potential of populations and result in more heterogeneous evolutionary outcomes. Evolutionary trajectories followed in small-bottlenecking regimes additionally suggest that the fitness landscape associated with persistence has a rugged topography, with distinct trajectories towards increased persistence that are accessible to evolving populations. Furthermore, sequencing data of evolved populations and knockout libraries after selection reveal various genes that are potentially involved in persistence, including previously known as well as novel targets. Together, our results do not only provide experimental evidence for evolutionary theories, but also contribute to a better understanding of the environmental and genetic factors that guide bacterial adaptation to antibiotic treatment.

Download Full-text

The evolutionary dynamics and fitness landscape of clonal hematopoiesis

Science ◽

10.1126/science.aay9333 ◽

2020 ◽

Vol 367 (6485) ◽

pp. 1449-1454 ◽

Cited By ~ 35

Author(s):

Caroline J. Watson ◽

A. L. Papula ◽

Gladys Y. P. Poon ◽

Wing H. Wong ◽

Andrew L. Young ◽

...

Keyword(s):

Evolutionary Dynamics ◽

Fitness Landscape ◽

Sequencing Data ◽

Driver Genes ◽

Single Nucleotide ◽

Hematopoietic Stem ◽

Clonal Hematopoiesis ◽

Fitness Advantage ◽

Pathogenic Variants ◽

Nucleotide Resolution

Somatic mutations acquired in healthy tissues as we age are major determinants of cancer risk. Whether variants confer a fitness advantage or rise to detectable frequencies by chance remains largely unknown. Blood sequencing data from ~50,000 individuals reveal how mutation, genetic drift, and fitness shape the genetic diversity of healthy blood (clonal hematopoiesis). We show that positive selection, not drift, is the major force shaping clonal hematopoiesis, provide bounds on the number of hematopoietic stem cells, and quantify the fitness advantages of key pathogenic variants, at single-nucleotide resolution, as well as the distribution of fitness effects (fitness landscape) within commonly mutated driver genes. These data are consistent with clonal hematopoiesis being driven by a continuing risk of mutations and clonal expansions that become increasingly detectable with age.

Download Full-text

The evolutionary dynamics and fitness landscape of clonal haematopoiesis

10.1101/569566 ◽

2019 ◽

Cited By ~ 5

Author(s):

Caroline J. Watson ◽

Alana Papula ◽

Yeuk P. G. Poon ◽

Wing H. Wong ◽

Andrew L. Young ◽

...

Keyword(s):

Evolutionary Dynamics ◽

Fitness Landscape ◽

Allele Frequencies ◽

Variant Allele ◽

Age Dependence ◽

Sequencing Data ◽

Fitness Effect ◽

Fitness Advantage ◽

Pathogenic Variants ◽

Cell Niche

Somatic mutations acquired in healthy tissues as we age are major determinants of cancer risk. Whether variants confer a fitness advantage or rise to detectable frequencies by chance, however, remains largely unknown. Here, by combining blood sequencing data from ∼50,000 individuals, we reveal how mutation, genetic drift and fitness differences combine to shape the genetic diversity of healthy blood (‘clonal haematopoiesis’). By analysing the spectrum of variant allele frequencies we quantify fitness advantages for key pathogenic variants and genes and provide bounds on the number of haematopoietic stem cells. Positive selection, not drift, is the major force shaping clonal haematopoiesis. The remarkably wide variation in variant allele frequencies observed across individuals is driven by chance differences in the timing of mutation acquisition combined with differences in the cell-intrinsic fitness effect of variants. Contrary to the widely held view that clonal haematopoiesis is driven by ageing-related alterations in the stem cell niche, the data are consistent with the age dependence being driven simply by continuing risk of mutations and subsequent clonal expansions that lead to increased detectability at older ages.

Download Full-text

Inference of clonal selection in cancer populations using single-cell sequencing data

Bioinformatics ◽

10.1093/bioinformatics/btz392 ◽

2019 ◽

Vol 35 (14) ◽

pp. i398-i407 ◽

Cited By ~ 2

Author(s):

Pavel Skums ◽

Viachaslau Tsyvina ◽

Alex Zelikovsky

Keyword(s):

Single Cell ◽

Cancer Progression ◽

Tumor Heterogeneity ◽

Evolutionary Dynamics ◽

Fitness Landscape ◽

Clonal Selection ◽

Fitness Landscapes ◽

Sequencing Data ◽

Single Cell Sequencing ◽

Insight Into

Abstract Summary Intra-tumor heterogeneity is one of the major factors influencing cancer progression and treatment outcome. However, evolutionary dynamics of cancer clone populations remain poorly understood. Quantification of clonal selection and inference of fitness landscapes of tumors is a key step to understanding evolutionary mechanisms driving cancer. These problems could be addressed using single-cell sequencing (scSeq), which provides an unprecedented insight into intra-tumor heterogeneity allowing to study and quantify selective advantages of individual clones. Here, we present Single Cell Inference of FItness Landscape (SCIFIL), a computational tool for inference of fitness landscapes of heterogeneous cancer clone populations from scSeq data. SCIFIL allows to estimate maximum likelihood fitnesses of clone variants, measure their selective advantages and order of appearance by fitting an evolutionary model into the tumor phylogeny. We demonstrate the accuracy our approach, and show how it could be applied to experimental tumor data to study clonal selection and infer evolutionary history. SCIFIL can be used to provide new insight into the evolutionary dynamics of cancer. Availability and implementation Its source code is available at https://github.com/compbel/SCIFIL.

Download Full-text

Laparoscopic appendectomy versus antibiotic treatment for acute appendicitis—a systematic review

International Journal of Colorectal Disease ◽

10.1007/s00384-021-03927-5 ◽

2021 ◽

Author(s):

Franziska Köhler ◽

Anne Hendricks ◽

Carolin Kastner ◽

Sophie Müller ◽

Kevin Boerner ◽

...

Keyword(s):

Systematic Review ◽

Antibiotic Therapy ◽

Antibiotic Treatment ◽

Laparoscopic Appendectomy ◽

Data Extraction ◽

Open Appendectomy ◽

Cochrane Library ◽

Pubmed Database ◽

Uncomplicated Appendicitis ◽

Absence From Work

Abstract Background Over the last years, laparoscopic appendectomy has progressively replaced open appendectomy and become the current gold standard treatment for suspected, uncomplicated appendicitis. At the same time, though, it is an ongoing discussion that antibiotic therapy can be an equivalent treatment for patients with uncomplicated appendicitis. The aim of this systematic review was to determine the safety and efficacy of antibiotic therapy and compare it to the laparoscopic appendectomy for acute, uncomplicated appendicitis. Methods The PubMed database, Embase database, and Cochrane library were scanned for studies comparing laparoscopic appendectomy with antibiotic treatment. Two independent reviewers performed the study selection and data extraction. The primary endpoint was defined as successful treatment of appendicitis. Secondary endpoints were pain intensity, duration of hospitalization, absence from work, and incidence of complications. Results No studies were found that exclusively compared laparoscopic appendectomy with antibiotic treatment for acute, uncomplicated appendicitis. Conclusions To date, there are no studies comparing antibiotic treatment to laparoscopic appendectomy for patients with acute uncomplicated appendicitis, thus emphasizing the lack of evidence and need for further investigation.

Download Full-text

Non-responder phenotype reveals apparent microbiome-wide antibiotic tolerance in the murine gut

Communications Biology ◽

10.1038/s42003-021-01841-8 ◽

2021 ◽

Vol 4 (1) ◽

Author(s):

Christian Diener ◽

Anna C. H. Hoge ◽

Sean M. Kearney ◽

Ulrike Kusebauch ◽

Sushmita Patwardhan ◽

...

Keyword(s):

Antibiotic Treatment ◽

Treatment Duration ◽

Efflux Transporters ◽

High Dose ◽

Specific Host ◽

Lactam Antibiotic ◽

Enteric Infections ◽

Community Tolerance ◽

Future Work ◽

Antibiotic Treatment Duration

AbstractBroad spectrum antibiotics cause both transient and lasting damage to the ecology of the gut microbiome. Antibiotic-induced loss of gut bacterial diversity has been linked to susceptibility to enteric infections. Prior work on subtherapeutic antibiotic treatment in humans and non-human animals has suggested that entire gut communities may exhibit tolerance phenotypes. In this study, we validate the existence of these community tolerance phenotypes in the murine gut and explore how antibiotic treatment duration or a diet enriched in antimicrobial phytochemicals might influence the frequency of this phenotype. Almost a third of mice exhibited whole-community tolerance to a high dose of the β-lactam antibiotic cefoperazone, independent of antibiotic treatment duration or dietary phytochemical amendment. We observed few compositional differences between non-responder microbiota during antibiotic treatment and the untreated control microbiota. However, gene expression was vastly different between non-responder microbiota and controls during treatment, with non-responder communities showing an upregulation of antimicrobial tolerance genes, like efflux transporters, and a down-regulation of central metabolism. Future work should focus on what specific host- or microbiome-associated factors are responsible for tipping communities between responder and non-responder phenotypes so that we might learn to harness this phenomenon to protect our microbiota from routine antibiotic treatment.

Download Full-text

Environmental changes dictate selection and nonspecific epistasis in an empirical phenotype-environment-fitness landscape

10.1101/2021.04.14.439889 ◽

2021 ◽

Author(s):

J.Z. Chen ◽

D.M. Fowler ◽

N. Tokuriki

Keyword(s):

Selection Pressure ◽

Evolutionary Dynamics ◽

Environmental Changes ◽

Fitness Landscape ◽

Resistance Level ◽

Phenotypic Changes ◽

Environmental Selection ◽

Selection Environment ◽

Data Points ◽

Environmental Dependence

SummaryThe fitness landscape, a function that maps genotypic and phenotypic changes to their effects on fitness, is an invaluable concept in evolutionary biochemistry. Though widely discussed, measurements of phenotype-fitness landscapes in proteins remain scarce. Here, we quantify all single mutational effects on fitness and phenotype (antibiotic resistance level) of VIM-2 β-lactamase (5600 variants) across a 64-fold range of ampicillin concentrations by deep mutational scanning. We then construct a phenotype-fitness landscape that takes variations in environmental selection pressure into account (a phenotype-environment-fitness landscape). We found that a simple, empirical landscape accurately models the ~39,000 mutational data points, which suggests the evolution of VIM-2 can be predicted based on the selection environment. Our landscape provides new quantitative knowledge on the evolution of the β-lactamases and proteins in general, particularly their evolutionary dynamics under sub-inhibitory antibiotic concentrations, as well as the mechanisms and environmental dependence of nonspecific epistasis.

Download Full-text

A Study of the Coevolution of Digital Organisms with an Evolutionary Cellular Automaton

Biology ◽

10.3390/biology10111147 ◽

2021 ◽

Vol 10 (11) ◽

pp. 1147

Author(s):

Javier Falgueras-Cano ◽

Juan-Antonio Falgueras-Cano ◽

Andrés Moya

Keyword(s):

Natural Selection ◽

Cellular Automaton ◽

Evolutionary Dynamics ◽

Evolutionary Strategy ◽

Phenotypic Flexibility ◽

Biological Interactions ◽

Fragmented Habitats ◽

Digital Organisms ◽

Effective Instrument ◽

Good Resource

This paper presents an Evolutionary Cellular Automaton (ECA) that simulates the evolutionary dynamics of biological interactions by manipulating strategies of dispersion and associations between digital organisms. The parameterization of the different types of interaction and distribution strategies using configuration files generates easily interpretable results. In that respect, ECA is an effective instrument for measuring the effects of relative adaptive advantages and a good resource for studying natural selection. Although ECA works effectively in obtaining the expected results from most well-known biological interactions, some unexpected effects were observed. For example, organisms uniformly distributed in fragmented habitats do not favor eusociality, and mutualism evolved from parasitism simply by varying phenotypic flexibility. Finally, we have verified that natural selection represents a cost for the emergence of sex by destabilizing the stable evolutionary strategy of the 1:1 sex ratio after generating randomly different distributions in each generation.

Download Full-text

A METAGENOMIC ASSESSMENT OF BACTERIAL CONTAMINATION OF DUST EVENTS IN SENEGAL

International Journal of Advanced Research ◽

10.21474/ijar01/12610 ◽

2021 ◽

Vol 9 (03) ◽

pp. 509-526

Author(s):

Alioune Marone ◽

◽

Malick Mbengue ◽

Gregory Jenkins ◽

Demba Ndao Niang ◽

...

Keyword(s):

Respiratory Diseases ◽

Rrna Gene ◽

Source Population ◽

Sequencing Analysis ◽

Human Pathogens ◽

Sequencing Data ◽

Bacterial Populations ◽

African Dust ◽

Hypervariable Regions ◽

Dust Events

Previous work in the Caribbean and West Africa have shown that air samples taken during dust events contain microorganisms (bacteria, fungi, viruses), including human pathogens that can cause many respiratory diseases. To better understand the potential downstream effect of bacteria dust on human health and public ecosystems, it is important to characterize the source population. In this study, we aimed to explore the bacterial populations of African dust samples collected between 2013-2017. The dust samples were collected using the spatula method, then the hypervariable regions (V3 and V4) of the 16S rRNA gene were amplified using PCR followed byMiSeq Illumina sequencing. Analysis of the sequencing data were performed using MG-RAST. At the phylum level, the proportions of Actinobacteria (22%), Firmicutes (20%), Proteobacteria (19%), and Bacteroidetes (13%) were respectively predominant in all dust samples. At the genus level, Bacillus(16%), Pseudomonas(10%), Nocardiodes and Exiguobacterium (5%) are the most dominated genera in African dust samples collected in this study.The study showed that molecular characterization of dust microbial population remains a very efficient method, also applicable to the search for viruses and fungi in this type of sample. It is important to note that the majority of microorganisms identified in this study can cause respiratory diseases.

Download Full-text

Urinary cytokines in women with refractory detrusor overactivity: A longitudinal study of rotating antibiotic versus placebo treatment

PLoS ONE ◽

10.1371/journal.pone.0247861 ◽

2021 ◽

Vol 16 (3) ◽

pp. e0247861

Author(s):

Zhuoran Chen ◽

Samantha Ognenovska ◽

Ronald Sluyter ◽

Kate H. Moore ◽

Kylie J. Mansfield

Keyword(s):

Antibiotic Therapy ◽

Receptor Antagonist ◽

Antibiotic Treatment ◽

Detrusor Overactivity ◽

Placebo Treatment ◽

Symptom Improvement ◽

Urinary Concentration ◽

Consecutive Series ◽

Tnf Α ◽

Patient Outcome Measures

Over 50% of women with detrusor overactivity (DO), who do not respond to therapy have been shown to have bacteriuria, which may stimulate the release of inflammatory cytokines than can enhance nerve signalling, leading to symptoms of urgency. This study made use of a consecutive series of urine samples collected from women with refractory DO, who participated in a clinical trial of rotating antibiotic therapy. The aim was to determine the effect of bacteriuria and antibiotic treatment on the levels of urinary cytokines, and to correlate the cytokine concentration with patient outcome measures relating to urgency or urge incontinence. The urinary cytokines chosen were IL-1α, IL-1 receptor antagonist, IL-4, IL-6, IL-8, IL-10, CXCL10 (IP-10), MCP-1 and TNF-α. The presence of bacteriuria stimulated a significant increase in the concentrations of IL-1α (P 0.0216), IL-1 receptor antagonist (P 0.0264), IL-6 (P 0.0003), IL-8 (P 0.0043) and CXCL-10 (P 0.009). Antibiotic treatment significantly attenuated the release of IL-1α (P 0.005), IL-6 (P 0.0027), IL-8 (P 0.0001), IL-10 (P 0.049), and CXCL-10 (P 0.042), i.e. the response to the presence of bacteria was less in the antibiotic treated patients. Across the 26 weeks of the trial, antibiotic treatment reduced the concentration of five of the nine cytokines measured (IL-1α, IL-6, IL-8, IL-10 and CXCL-10); this did not reach significance at every time point. In antibiotic treated patients, the urinary concentration of CXCL-10 correlated positively with four of the six measures of urgency. This study has shown that cytokines associated with activation of the innate immune system (e.g. cytokines chemotactic for or activators of macrophages and neutrophils) are reduced by antibiotic therapy in women with refractory DO. Antibiotic therapy is also associated with symptom improvement in these women, therefore the inflammatory response may have a role in the aetiology of refractory DO.

Download Full-text

The distribution of epistasis on simple fitness landscapes

10.1101/490573 ◽

2018 ◽

Author(s):

Christelle Fraïsse ◽

John J. Welch

Keyword(s):

Evolutionary Dynamics ◽

Fitness Landscape ◽

Null Model ◽

Large Data ◽

Fitness Landscapes ◽

Mutational Bias ◽

Data Set ◽

Epistatic Interactions ◽

Standing Variation ◽

Mean And Variance

AbstractFitness interactions between mutations can influence a population’s evolution in many different ways. While epistatic effects are difficult to measure precisely, important information about the overall distribution is captured by the mean and variance of log fitnesses for individuals carrying different numbers of mutations. We derive predictions for these quantities from simple fitness landscapes, based on models of optimizing selection on quantitative traits. We also explore extensions to the models, including modular pleiotropy, variable effects sizes, mutational bias, and maladaptation of the wild-type. We illustrate our approach by reanalysing a large data set of mutant effects in a yeast snoRNA. Though characterized by some strong epistatic interactions, these data give a good overall fit to the non-epistatic null model, suggesting that epistasis might have little effect on the evolutionary dynamics in this system. We also show how the amount of epistasis depends on both the underlying fitness landscape, and the distribution of mutations, and so it is expected to vary in consistent ways between new mutations, standing variation, and fixed mutations.

Download Full-text