Adaptive landscapes of antibiotic resistance: population size and 'survival-of-the-flattest'.
Lead Research Organisation:
University of Manchester
Department Name: Earth Atmospheric and Env Sciences
Abstract
Spontaneous mutation altering genetic sequences is a key engine of evolution. However, if the rate of mutations exceeds a 'critical mutation rate', changes occur too frequently for natural selection to maintain the population's genetic makeup. For example, one can think of mutation as moving offspring away from their parents in a 'fitness landscape' where peaks are genetic sequences with high fitness. If there is too much mutation (above a critical mutation rate), selection may be able to keep a population on a broad fitness peak, but not on a narrow one, so-called 'survival-of-the-flattest'. Such critical mutation rates are generally believed to be much higher than those seen in typical biological organisms. However, we have recently discovered that, in computer simulations, critical mutation rates are much lower in very small populations (<100 individuals). This suggests that survival-of-the-flattest could be occurring within the normal range of biological mutation rates.
This proposal therefore aims to test whether survival-of-the-flattest really does occur in biology, using antibiotic resistance evolution as a test case. This requires an integrated, multi-disciplinary approach, conducting decisive wet-lab experiments, aligning computer simulations with biology and developing a rigorous and predictive theoretical framework that relates findings to mathematical understanding. Our first objective will be to characterise the fitness landscapes of bacteria resistant to different antibiotics to determine whether appropriate distinctions exist in practice between narrow and broad fitness peaks. Here we will focus on environments containing antibiotics, but will use experimental evolution (at high and minimal population sizes) with complete genome sequencing to consider mutations across the genome. Our second Objective is to develop computer simulations and theory to align with the biology. Specifically we need to relate our findings about critical mutation rates in simulations to existing theory. We then need to move both theory and simulation towards more biologically realistic assumptions. For instance we shall test more realistic fitness landscapes, particularly those determined empirically through our first Objective. Our final Objective is rigorously to test the coherence of the theory, simulation and biological experiment with each other. In particular we shall use experimental evolution at small population sizes to test whether we can detect the effect of critical mutation rates as predicted and further characterise the experimentally evolved strains to test the consistency of biological mechanisms involved.
Rigorously unpicking this novel population size effect in the evolution of antibiotic resistance could have broad impacts. Antibiotic resistant bacteria inevitably appear by mutation with a small population size and bacteria resistant to one antibiotic will be knocked down to small population sizes by another. The hypotheses we shall test here will determine whether the maintenance of particular antibiotic resistances at such small population sizes, could depend on the details of the different fitness landscapes imposed by different antibiotics in a theoretically predictable way - potentially crucial information in combatting antimicrobial resistance.
In sum this work will closely link experimental approaches to evolution in biology, simulation and theory to determine if when and how survival-of-the-flattest impinges on the increasingly critical issue of antibiotic resistance evolution.
This proposal therefore aims to test whether survival-of-the-flattest really does occur in biology, using antibiotic resistance evolution as a test case. This requires an integrated, multi-disciplinary approach, conducting decisive wet-lab experiments, aligning computer simulations with biology and developing a rigorous and predictive theoretical framework that relates findings to mathematical understanding. Our first objective will be to characterise the fitness landscapes of bacteria resistant to different antibiotics to determine whether appropriate distinctions exist in practice between narrow and broad fitness peaks. Here we will focus on environments containing antibiotics, but will use experimental evolution (at high and minimal population sizes) with complete genome sequencing to consider mutations across the genome. Our second Objective is to develop computer simulations and theory to align with the biology. Specifically we need to relate our findings about critical mutation rates in simulations to existing theory. We then need to move both theory and simulation towards more biologically realistic assumptions. For instance we shall test more realistic fitness landscapes, particularly those determined empirically through our first Objective. Our final Objective is rigorously to test the coherence of the theory, simulation and biological experiment with each other. In particular we shall use experimental evolution at small population sizes to test whether we can detect the effect of critical mutation rates as predicted and further characterise the experimentally evolved strains to test the consistency of biological mechanisms involved.
Rigorously unpicking this novel population size effect in the evolution of antibiotic resistance could have broad impacts. Antibiotic resistant bacteria inevitably appear by mutation with a small population size and bacteria resistant to one antibiotic will be knocked down to small population sizes by another. The hypotheses we shall test here will determine whether the maintenance of particular antibiotic resistances at such small population sizes, could depend on the details of the different fitness landscapes imposed by different antibiotics in a theoretically predictable way - potentially crucial information in combatting antimicrobial resistance.
In sum this work will closely link experimental approaches to evolution in biology, simulation and theory to determine if when and how survival-of-the-flattest impinges on the increasingly critical issue of antibiotic resistance evolution.
Technical Summary
We have recently identified a dramatic drop, at low population sizes, in critical mutation rates. Above these rates a narrow fitness peak may be lost while a broad fitness peak is maintained in a population i.e. 'survival-of-the-flattest'. This brings such thresholds into the range of actual biological mutation rates. This effect could be important in determining evolutionary trajectories, e.g. in the evolution of antibiotic resistance. We therefore propose to test if such effects occur in practice. This requires a multi-disciplinary approach to develop and integrate wet-lab experimental evolution, computer simulation and theory. In the wet-lab we shall evolve Escherichia coli resistant to different antibiotics. Evolution at high population sizes will climb adaptive peaks, at minimal population sizes (mutation accumulation) will move down them and complete genome sequencing will determine the numbers of peaks involved. In simulations we shall develop state-of-the-art GPGPU implementations to relax various biologically unrealistic assumptions in current models. Thus we shall test e.g. the population size dependence in biologically realistic fitness landscapes. At the same time we shall develop existing theory of error thresholds to address critical mutation rates, finite, small populations and more biologically realistic fitness landscapes. We shall test the integration of theory, simulation and biology through close feedback between theory and simulation, experimental evolution at small but not minimal population sizes and detailed tests on specific mutations to identify pleiotropic effects. Together this will test the potential role of the relationship between population size and mutation rate thresholds in biology. This has the potential to link a well-established area of theory and simulation much more closely with biology and to bring timely, critical and novel insights into the crucial area of anti-microbial resistance evolution.
Planned Impact
Who will benefit from this research?
Beneficiaries will include:
a) The wider scientific community and those who benefit from their research. This applies particularly to those with interests in antibiotics, healthcare policy, population genetics and evolutionary dynamics of small populations, conservation biology, evolutionary algorithms, genetic search, problem solving using biologically inspired genetic algorithms, and interdisciplinary approaches to biology.
b) The researcher Co-I and PDRA employed on the project.
c) Members of the wider public with interests in antibiotics, healthcare, medicine, evolution and conservation.
d) All those involved in dealing with the current crises in antibiotic resistance (ultimately all who will benefit from the use of antibiotics which are currently becoming unusable due to the evolution of antibiotic resistant microbes).
e) Charities and organisations with an interest in developing conservation strategies and understanding the threats to populations at risk of extinction.
How will they benefit?
a) The wider scientific community will benefit as outlined in the Academic Beneficiaries section.
b) The researcher Co-I and PDRA will benefit from training, both in the general practicalities of cross-disciplinary research and, in the case of the researcher-Co-I, specific training in a next-generation sequence analysis (see Pathways to Impact).
c) As we have discovered through our existing work on antibiotic resistance, the wider public have strong interests in issues surrounding antibiotic resistant microbes and their evolution. This research will shed new light on this issue in terms of the role of mutation, population size and the effects of different fitness landscapes. They will benefit by gaining a deepening of understanding of the fundamental science behind the current crisis. Beyond that, this relevance offers a route in to inspiring interest in a range of STEM subjects and the interaction between them, providing a real world case study emphasising their importance to society
d) In the long-term this research could impact healthcare strategy through drug regime policy. Specifically, the use of combinations of antibiotics is becoming increasingly important and, depending on the results of this project, it may become clear that mutation rates and available evolutionary trajectories, in combination with population size, will result in predictably different outcomes if antibiotics are applied in different regimes.
e) Here we investigate fundamental theoretical issues of small population size and whether they are truly relevant to biological systems. While we use antibiotic resistant microbes as a tractable system, if we discover biological relevance, this will be applicable to animals as much as microbes. Therefore all those concerned with organisms at small population sizes, e.g. conservation organisations, could ultimately benefit from this work in uncovering the effect of mutation that could be cryptically causing endangered organisms to lose fit alleles, thereby influencing both conservation practice and policy.
Beneficiaries will include:
a) The wider scientific community and those who benefit from their research. This applies particularly to those with interests in antibiotics, healthcare policy, population genetics and evolutionary dynamics of small populations, conservation biology, evolutionary algorithms, genetic search, problem solving using biologically inspired genetic algorithms, and interdisciplinary approaches to biology.
b) The researcher Co-I and PDRA employed on the project.
c) Members of the wider public with interests in antibiotics, healthcare, medicine, evolution and conservation.
d) All those involved in dealing with the current crises in antibiotic resistance (ultimately all who will benefit from the use of antibiotics which are currently becoming unusable due to the evolution of antibiotic resistant microbes).
e) Charities and organisations with an interest in developing conservation strategies and understanding the threats to populations at risk of extinction.
How will they benefit?
a) The wider scientific community will benefit as outlined in the Academic Beneficiaries section.
b) The researcher Co-I and PDRA will benefit from training, both in the general practicalities of cross-disciplinary research and, in the case of the researcher-Co-I, specific training in a next-generation sequence analysis (see Pathways to Impact).
c) As we have discovered through our existing work on antibiotic resistance, the wider public have strong interests in issues surrounding antibiotic resistant microbes and their evolution. This research will shed new light on this issue in terms of the role of mutation, population size and the effects of different fitness landscapes. They will benefit by gaining a deepening of understanding of the fundamental science behind the current crisis. Beyond that, this relevance offers a route in to inspiring interest in a range of STEM subjects and the interaction between them, providing a real world case study emphasising their importance to society
d) In the long-term this research could impact healthcare strategy through drug regime policy. Specifically, the use of combinations of antibiotics is becoming increasingly important and, depending on the results of this project, it may become clear that mutation rates and available evolutionary trajectories, in combination with population size, will result in predictably different outcomes if antibiotics are applied in different regimes.
e) Here we investigate fundamental theoretical issues of small population size and whether they are truly relevant to biological systems. While we use antibiotic resistant microbes as a tractable system, if we discover biological relevance, this will be applicable to animals as much as microbes. Therefore all those concerned with organisms at small population sizes, e.g. conservation organisations, could ultimately benefit from this work in uncovering the effect of mutation that could be cryptically causing endangered organisms to lose fit alleles, thereby influencing both conservation practice and policy.
Organisations
People |
ORCID iD |
Christopher Knight (Principal Investigator) |
Publications
Aston E
(2017)
Critical Mutation Rate has an Exponential Dependence on Population Size for Eukaryotic-length Genomes with Crossover.
in Scientific reports
Aston E.
(2016)
Critical mutation rate has an exponential dependence on population size for eukaryotic-length genomes
in Proceedings of the Artificial Life Conference 2016, ALIFE 2016
Aston E.
(2017)
Critical Mutation Rate in a Population with Horizontal Gene Transfer
in Proceedings of the 14th European Conference on Artificial Life, ECAL 2017
Belavkin RV
(2016)
Monotonicity of fitness landscapes and mutation rate control.
in Journal of mathematical biology
Gifford D
(2023)
Mutators can drive the evolution of multi-resistance to antibiotics
in PLOS Genetics
Gifford D
(2019)
Mutators drive evolution of multi-resistance to antibiotics
Gifford DR
(2018)
Environmental pleiotropy and demographic history direct adaptation under antibiotic selection.
in Heredity
Knight C
(2019)
Measuring Microbial Mutation Rates with the Fluctuation Assay
in Journal of Visualized Experiments
Krašovec R
(2018)
Opposing effects of final population density and stress on Escherichia coli mutation rate.
in The ISME journal
Krašovec R
(2017)
Spontaneous mutation rate is a plastic trait associated with population density across domains of life.
in PLoS biology
Description | We have developed new understanding of the evolution of antibiotic resistant bacteria in the presence of antibiotics and how that depends on different population sizes. While some of the work still needs development for publication, we have discovered, through a mixture of wet-lab experiments and computational models, how it is possible for populations to gain resistance to two drugs applied at the same time, when it is only possible to acquire those resistances one at a time. In particular we have shown how this depends on population sizes, and rates of mutation to resistance. |
Exploitation Route | When fully published, these findings will be of broad interest. They are already being taken forwards in terms of bringing them closer to medical application by Danna Gifford (originally postdoc on this grant) via her MRC (UKRI) fellowship. |
Sectors | Environment,Pharmaceuticals and Medical Biotechnology |
Description | By adding to the fundamental understanding of the evolutionary processes underlying the antimicrobial resistance crisis, we (via the activities recorded in other sections) are contributing to the very current and public debate around the best approaches to tackling this issue. |
Impact Types | Societal |
Description | EMBO Short Term Fellowship |
Amount | € 6,245 (EUR) |
Funding ID | 642 - 2014 |
Organisation | European Molecular Biology Organisation |
Sector | Charity/Non Profit |
Country | Germany |
Start | 04/2015 |
End | 07/2015 |
Description | Future Leaders fellowship: Spatio-temporal dynamics of mutation avoidance and antimicrobial resistance |
Amount | £990,098 (GBP) |
Funding ID | MR/T021225/1 |
Organisation | United Kingdom Research and Innovation |
Department | Future Leaders Research Fellowship |
Sector | Public |
Country | United Kingdom |
Start | 03/2020 |
End | 03/2024 |
Description | Meeting Attendance Grant |
Amount | € 400 (EUR) |
Organisation | Federation of European Microbiological Societies (FEMS) |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 07/2017 |
End | 08/2017 |
Description | Research Experience Placement studentship |
Amount | £2,500 (GBP) |
Organisation | Biotechnology and Biological Sciences Research Council (BBSRC) |
Sector | Public |
Country | United Kingdom |
Start | 06/2017 |
End | 09/2017 |
Description | Research Experience Placement studentship for Ella Marshal |
Amount | £2,500 (GBP) |
Organisation | Biotechnology and Biological Sciences Research Council (BBSRC) |
Sector | Public |
Country | United Kingdom |
Start | 06/2018 |
End | 09/2018 |
Description | SEES seedcorn funding |
Amount | £401 (GBP) |
Organisation | University of Manchester |
Sector | Academic/University |
Country | United Kingdom |
Start | 02/2017 |
End | 07/2017 |
Description | Summer biomedical vacation scholarship for David Lever |
Amount | £2,000 (GBP) |
Organisation | Wellcome Trust |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 06/2018 |
End | 09/2018 |
Description | Tackling antimicrobial resistance by understanding evolutionary landscapes |
Amount | £251,000 (GBP) |
Funding ID | 204796/Z/16/Z |
Organisation | Wellcome Trust |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 06/2018 |
End | 07/2021 |
Description | Travel Grant |
Amount | £615 (GBP) |
Organisation | Microbiology Society |
Sector | Learned Society |
Country | United Kingdom |
Start | 06/2017 |
End | 07/2017 |
Description | UKRI Innovation Fellowship |
Amount | £321,263 (GBP) |
Funding ID | MR/R024936/1 |
Organisation | Medical Research Council (MRC) |
Sector | Public |
Country | United Kingdom |
Start | 11/2017 |
End | 11/2020 |
Description | Wellcome Trust ISSF Strategic Awards in Single Cell Research |
Amount | £11,922 (GBP) |
Funding ID | 105610/Z/14/Z |
Organisation | Wellcome Trust |
Department | Wellcome Trust Institutional Strategic Support Fund |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 07/2016 |
End | 07/2017 |
Description | Wellome Trust ISSF Bridging Support |
Amount | £11,487 (GBP) |
Funding ID | 105610/Z/14/Z |
Organisation | Wellcome Trust |
Department | Wellcome Trust Institutional Strategic Support Fund |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 02/2017 |
End | 04/2017 |
Description | Dragonfly day |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Schools |
Results and Impact | Dragonfly day STEM speed networking event for Girls in Year 8/9 |
Year(s) Of Engagement Activity | 2017 |
Description | Frontiers in Science talk |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Undergraduate students |
Results and Impact | Invited general talk in the 'Frontiers in Science' series about research (specifically BBSRC-funded grants) to 1st and 2nd year undergraduates. Very constructive engagement in discussion and follow-up regarding future lab placements. |
Year(s) Of Engagement Activity | 2017 |
Description | I'm a scientist--get me out of here |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Schools |
Results and Impact | Postdoc Danna Gifford was one of 5 scientists in the 'Antibiotics Zone' of the online " X Factor-style competition between scientists, where students are the judges." Over 400 students from 14 schools were actively logged in, asking over 400 questions, resulting in over 600 answers and over 5000 lines of live chat. Danna won 3rd place, being equal top contributor with the winner to the live chats. Further details of Danna's participation available here: http://antibioj16.imascientist.org.uk/profile/dannagifford/ |
Year(s) Of Engagement Activity | 2017 |
URL | http://about.imascientist.org.uk/files/2016/07/Antibiotics-Zone-Report-J16.pdf |
Description | Media engagement around PLOS Biology paper |
Form Of Engagement Activity | A press release, press conference or response to a media enquiry/interview |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Media (as a channel to the public) |
Results and Impact | Press release and wider media engagement around our 2017 PLOS Biology paper. This generated substantial interest, including over 44,000 impressions for my first tweet on the subject and over 800 profile views over the course of 2 weeks. |
Year(s) Of Engagement Activity | 2017 |
URL | http://www.manchester.ac.uk/discover/news/antibiotic-resistance-rises-in-lonely-mutating-microbes/ |
Description | School Visit |
Form Of Engagement Activity | Participation in an open day or visit at my research institution |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Schools |
Results and Impact | Organised lab visit for Rochdale Sixth Form College science students, involving presentations and discussions with researchers, feeding into the students' imminent decisions about higher education. |
Year(s) Of Engagement Activity | 2017 |
Description | University of Manchester Community Festival 2017 |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Public/other audiences |
Results and Impact | We had a stand at the University 'community festival', "Experimenting with Evolution" at which we talked about our research (PI and postdoc on this grant) and got people to compete in evolving better digital organisms in computer simulations. |
Year(s) Of Engagement Activity | 2018 |
URL | http://www.socialresponsibility.manchester.ac.uk/strategic-priorities/engaging-our-communities/publi... |