---
_id: '6263'
abstract:
- lang: eng
text: 'Antibiotic resistance can emerge spontaneously through genomic mutation and render
treatment ineffective. To counteract this process, in addition to the discovery and
description of resistance mechanisms,a deeper understanding of resistanceevolvabilityand
its determinantsis needed. To address this challenge, this thesisuncoversnew genetic
determinants of resistance evolvability using a customized robotic setup,
exploressystematic ways in which resistance evolution is perturbed due to
dose-responsecharacteristics of drugs and mutation rate differences,and mathematically investigates
the evolutionary fate of one specific type of evolvability modifier -a stress-induced
mutagenesis allele.We find severalgenes which strongly inhibit or potentiate resistance evolution. In order
to identify them, we first developedan automated high-throughput feedback-controlled
protocol whichkeeps the population size and selection pressure approximately constant
for hundreds of cultures by dynamically re-diluting the cultures and adjusting the antibiotic
concentration. We implementedthis protocol on a customized liquid handling robot and
propagated 100 different gene deletion strains of Escherichia coliin triplicate for over 100
generations in tetracycline and in chloramphenicol, and comparedtheir adaptation rates.We find a diminishing returns pattern, where initially sensitive strains adapted more
compared to less sensitive ones. Our data uncover that deletions of certain genes
which do not affect mutation rate,including efflux pump components, a chaperone and
severalstructural and regulatory genes can strongly and reproducibly alterresistance evolution.
Sequencing analysis of evolved populations indicates that epistasis with resistance
mutations is the most likelyexplanation. This work could inspire treatment strategies in
which targeted inhibitors of evolvability mechanisms will be given alongside antibiotics to
slow down resistance evolution and extend theefficacy of antibiotics.We implemented astochasticpopulation genetics model,
toverifyways in which general properties, namely, dose-response characteristics of drugs and mutation rates, influence
evolutionary dynamics. In particular, under the exposure to antibiotics with shallow dose-response curves,bacteria have narrower distributions of fitness effects of new mutations.
We show that in silicothis also leads to slower resistance evolution. We
see and confirm with experiments that increased mutation rates, apart from speeding
up evolution, also leadto high reproducibility of phenotypic adaptation in a context
of continually strong selection pressure.Knowledge of these patterns can aid in predicting the dynamics of antibiotic
resistance evolutionand adapting treatment schemes accordingly.Focusing on a previously described type of evolvability modifier
–a stress-induced mutagenesis allele –we find conditions under which it can persist in a population under
periodic selectionakin to clinical treatment. We set up a deterministic
infinite populationcontinuous time model tracking the frequencies of a mutator and resistance allele and
evaluate various treatment schemes in how well they maintain a stress-induced
mutator allele. In particular,a high diversity of stresses is crucial for the persistence
of the mutator allele. This leads to a general trade-off where exactly those
diversifying treatment schemes which are likely to decrease levels of resistance could lead to stronger selection of highly
evolvable genotypes.In the long run, this work will lead to a deeper understanding of the genetic and cellular
mechanisms involved in antibiotic resistance evolution and could inspire new strategies
for slowing down its rate. '
acknowledged_ssus:
- _id: M-Shop
- _id: LifeSc
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Marta
full_name: Lukacisinova, Marta
id: 4342E402-F248-11E8-B48F-1D18A9856A87
last_name: Lukacisinova
orcid: 0000-0002-2519-8004
citation:
ama: Lukacisinova M. Genetic determinants of antibiotic resistance evolution. 2018.
doi:10.15479/AT:ISTA:th1072
apa: Lukacisinova, M. (2018). Genetic determinants of antibiotic resistance evolution.
Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:th1072
chicago: Lukacisinova, Marta. “Genetic Determinants of Antibiotic Resistance Evolution.”
Institute of Science and Technology Austria, 2018. https://doi.org/10.15479/AT:ISTA:th1072.
ieee: M. Lukacisinova, “Genetic determinants of antibiotic resistance evolution,”
Institute of Science and Technology Austria, 2018.
ista: Lukacisinova M. 2018. Genetic determinants of antibiotic resistance evolution.
Institute of Science and Technology Austria.
mla: Lukacisinova, Marta. Genetic Determinants of Antibiotic Resistance Evolution.
Institute of Science and Technology Austria, 2018, doi:10.15479/AT:ISTA:th1072.
short: M. Lukacisinova, Genetic Determinants of Antibiotic Resistance Evolution,
Institute of Science and Technology Austria, 2018.
date_created: 2019-04-09T13:57:15Z
date_published: 2018-12-28T00:00:00Z
date_updated: 2023-09-22T09:20:37Z
day: '28'
ddc:
- '570'
- '576'
- '579'
degree_awarded: PhD
department:
- _id: ToBo
doi: 10.15479/AT:ISTA:th1072
file:
- access_level: open_access
checksum: fc60585c9eaad868ac007004ef130908
content_type: application/pdf
creator: dernst
date_created: 2019-04-09T13:49:24Z
date_updated: 2021-02-11T11:17:17Z
embargo: 2020-01-25
file_id: '6264'
file_name: 2018_Thesis_Lukacisinova.pdf
file_size: 5656866
relation: main_file
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content_type: application/vnd.openxmlformats-officedocument.wordprocessingml.document
creator: dernst
date_created: 2019-04-09T13:49:23Z
date_updated: 2020-07-14T12:47:25Z
embargo_to: open_access
file_id: '6265'
file_name: 2018_Thesis_Lukacisinova_source.docx
file_size: 5168054
relation: source_file
file_date_updated: 2021-02-11T11:17:17Z
has_accepted_license: '1'
language:
- iso: eng
month: '12'
oa: 1
oa_version: Published Version
page: '91'
publication_identifier:
issn:
- 2663-337X
publication_status: published
publisher: Institute of Science and Technology Austria
related_material:
record:
- id: '1619'
relation: part_of_dissertation
status: public
- id: '696'
relation: part_of_dissertation
status: public
- id: '1027'
relation: part_of_dissertation
status: public
status: public
supervisor:
- first_name: Tobias
full_name: Bollenbach, Tobias
id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87
last_name: Bollenbach
orcid: 0000-0003-4398-476X
title: Genetic determinants of antibiotic resistance evolution
type: dissertation
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
year: '2018'
...