Document Type
Dissertation - Open Access
Award Date
2022
Degree Name
Doctor of Philosophy (PhD)
Department / School
Biology and Microbiology
First Advisor
Nicholas Butzin
Keywords
Antibiotic persistence, Antibiotic resistance, Fluctuation test, Minimal cell, Prime cell
Abstract
This work combines microbiology, molecular biology, Next-Generation Sequencing and system biology approaches to explore the mechanism of antibiotic persistence: a multi-drug tolerant, non-dividing, and metabolically altered state present in a subpopulation of cells due to phenotypic diversity rather than genetic variation (i.e. mutations). Persister can survive lethal antibiotic state and resuscitate after the treatment period is over. They are considered as the major contributing factor behind recurring infections. They also have a high mutation rate, which increases the chances of bacteria gaining antibiotic resistance. The formation of this phenotypic variant (persister) threatens the therapeutic effectiveness of antibiotics and understanding how bacteria form these heterogenic populations is critical for the development of new therapies. The molecular mechanisms underlying persistence are varied and debated in the literature. To probe this phenomena, I have explored three fundamental questions in this study related to antibiotic persistence, 1) when do persister cells form, do they form in response to the stress or are some cells prepared for stress (Chapter 2); 2) how do they go into this metabolically altered state and maintain this state for long-term antibiotic treatment (Chapter 3); 3) Is persistence an essential mechanism for bacteria and if so, does a minimal cell form persisters (Chapter 4)? There is much controversy in the literature when do these phenotypic variants (persister) form. To understand this, I have taken a novel approach to explore bacterial heterogeneity using a powerful fluctuation test (FT) framework to infer transient cell states that arise via reversible and non-genetic mechanisms to find hidden features of bacterial persistence. The FT was first pioneered ~80 years ago when Luria & Delbrück demonstrated that genetic mutations arise randomly in the absence of selection but not in response to the selection. They were studying phage (bacterial virus) infection. At the time of their work, it was debated whether mutations leading to resistance were directly induced by the virus (Lamarckian theory), or if they arose randomly in the population before viral infection (Darwinian theory). Their result showed genetic mutations arise randomly in the absence of selection, validating the Darwinian theory of evolution and led to a Nobel Prize in 1969. Our bacterial persister work is quite similar. Instead of studying mutations, we are exploring the existence of primed cells (a heterogeneously distinct subpopulation) before treatment that allow for long-term survival after treatment. Using the FT, we tested the variation between clonal populations that originated from an identical clone and showed that a subset of the population has an epigenetic "memory" that primes cells for persistence. We support our results with experimental benchwork and mathematical models. I am the first to definitively demonstrate that some cells are prepared in the population through a stochastic mechanism that enters into persistence in response to stress. Our work highly suggests that phenotypic heterogeneity is not entirely a random event resulting from stochastic noise in gene expression. Instead, it can develop from a rare, transiently inherited gene expression event. Another most argued topic in persister research field is whether persister cells transcribe during this non-dividing state in response to stress. To understand this, we isolate RNA from persister subpopulation at different time-points and compare the persister transcriptome profile with before antibiotic treated culture. Our analysis of RNAsequencing data demonstrates that persisters actively transcribe and translate proteins and they use multiple regulatory pathways to enter and maintain this altered state during antibiotic treatment. From our transcriptome analysis, we have selected seven uncharacterized genes which upregulated in persister cell and observed their effect on persister survival by overexpressing or making knockouts of those genes. When we overexpressed the hypothetical genes, most of them cause the growth defect and some of them put the cells into sleepy state for several hours. Our knockout mutants decrease the persister level dramatically by ~4-6 fold and ~10-15 fold at 3 h and 6h of Amp treatment, respectively. However, at 24 h, it showed no significant difference in survival from wild type which again showed that the persister transcriptome adjusts its expression profile over time. This result demonstrated that persisters alter their transcriptome to maintain their survival over the long-term antibiotic treatment. This research is particularly important, because researchers in persister field still argued over this and often cited dormancy is the primary method of persister survival. Another exciting study I have done where we used a minimal cell Mycoplasma mycoides JCVI-syn3B, contains only 491 genes and most of them are essential genes. We demonstrated that this minimal cell persists against multiple antibiotics although it contains a few already identified persister-related genes, whereas lacking many systems previously linked to persistence (e.g. ribosome hibernation genes). We also found that Syn3B evolves antibiotic resistance to different types of antibiotics expeditiously. Overall, in this study I explored the regulatory mechanisms that allow persisters to survive long-term antibiotic treatments. This work will impact our fundamental knowledge about antibiotic survival and set the groundwork for developing more effective therapeutics for recurrent bacterial infections.
Library of Congress Subject Headings
Antibiotics.
Persistence.
Drug resistance in microorganisms.
Number of Pages
113
Publisher
South Dakota State University
Recommended Citation
Hossain, Tahmina, "Decoding the Mystery of Antibiotic Persistence" (2022). Electronic Theses and Dissertations. 463.
https://openprairie.sdstate.edu/etd2/463