Klinicky Významné Rezistentní Plazmidy – Studium Biologické Zátěže a Stability Úspěšných Mobilních Genetických Elementů

MASARYKOVA UNIVERZITA

PŘÍRODOVĚDECKÁ FAKULTA

ÚSTAV EXPERIMENTÁLNÍ BIOLOGIE

Klinicky významné rezistentní plazmidy – studium biologické zátěže a stability úspěšných mobilních genetických elementů

Diplomová práce

Tomáš Nohejl

Vedoucí práce: doc. RNDr. Monika Dolejská, Ph.D. Brno 2018

Bibliografický záznam

Autor: Bc. Tomáš Nohejl

Přírodovědecká fakulta, Masarykova univerzita

Ústav experimentální biologie

Název práce: Klinicky významné rezistentní plazmidy – studium biologické zátěže a stability úspěšných mobilních genetických elementů

Studijní program: Experimentální biologie

Studijní obor: Molekulární biologie a genetika

Vedoucí práce: doc. RNDr. Monika Dolejská, Ph.D.

Akademický rok: 2017/2018

Počet stran 78

Klíčová slova: Antibiotická rezistence; plazmid; horizontální přenos genetické informace; HGT; konjugace; PMQR; chinolony; fitness; perzistence

Bibliographic entry

Author: Bc. Tomáš Nohejl

Faculty of Science, Masaryk University

Department of Experimental Biology

Title of Thesis: Clinically important resistance plasmids - the study of biological burden and stability of successful mobile genetic elements

Degree programme: Experimental biology

Field of Study: Molecular Biology and Genetics

Supervisor: doc. RNDr. Monika Dolejská, Ph.D.

Academic Year: 2017/2018

Number of Pages: 78

Keywords: Antibiotic resistance; plasmid; horizontal gene transfer; HGT; conjugation; PMQR; quinolones; fitness; persistence

Abstrakt

Antibiotická rezistence představuje jeden z nejzávažnějších globálních problémů současnosti. Šíření genů kódující antibiotickou rezistenci je zprostředkováno mobilními genetickými elementy, zejména pak konjugací plazmidů. Aby se předešlo případné krizi neefektivních antibiotik a rozšíření infekcí způsobených rezistentními bakteriemi, je nutná znalost vlastností a chování plazmidů. Práce je zaměřena na IncX skupinu plazmidů nesoucí geny pro plazmidově přenášenou rezistenci k chinolonům (PMQR). Cílem práce je odhalit trendy přenosu plazmidů skupiny IncX a zátěže a perzistence v hostitelských bakteriích několika druhů za různých podmínek.

Frekvence přenosu byla stanovena jako poměr počtu transkonjugantů na počet recipient. Byly zjištěny signifikantní rozdíly mezi jednotlivými IncX plazmidy, jejich bakteriálními hostiteli i fázemi růstu ve prospěch podskupiny IncX1. Analýza růstových křivek prokázala, že přítomnost IncX plazmidu negativně ovlivňuje fitness hostitelské bakterie, a to především v počátečních fázích růstu. Dlouhodobý kultivační experiment poukázal na perzistenci rezistentního plazmidu i za podmínek, kdy by neměl být pro bakteriální buňku v prostředí bez antibiotik potřebný. Tato práce ukazuje na významné vlastnosti IncX plazmidů nesoucích geny antibiotické rezistence, které pravděpodobně hrají úlohu v jejich šíření a udržování v bakteriálních populacích. Předmětem dalšího výzkumu by měl být detailní popis mechanismů, které stojí za trendy pozorovanými v této diplomové práci.

Abstract

Antibiotic resistance represents one of the most serious global issues of present. Dissemination of genes encoding for antibiotic resistance is mediated by mobile genetic elements, in particular by conjugation of plasmids. In order to prevent possible crisis of ineffective antibiotics and spread of infections caused by resistant bacteria, knowledge of the plasmid characteristics and behaviour is necessary. Thesis is focused on IncX group of plasmids carrying genes for plasmid-mediated quinolone resistance (PMQR). The aim of this thesis is to reveal the trends of IncX plasmid transfer and burden and persistence within host bacteria of several species under distinct conditions.

The frequency of transfer was determined as the ratio of the number of transconjugants to the number of recipients. Significant differences were found between the individual IncX plasmids, their bacterial hosts, and the phases of growth in favour of the IncX1 subgroup. Analysis of growth curves has shown that the presence of IncX plasmid negatively affects the fitness of host bacteria, especially in the early phases of growth. A long-term cultivation experiment pointed out the persistence of a resistant plasmid even in antibiotic-free environment where it should not be needed for a bacterial cell. This thesis shows the significant properties of IncX plasmids carrying antibiotic resistance genes that are likely to play a role in their dissemination and stability in bacterial populations. The subject of further research should be a detailed description of the mechanisms that are behind the trends observed in this diploma thesis.

Poděkování

Na tomto místě bych rád poděkoval mé vedoucí doc. RNDr. Monice Dolejské, Ph.D. za její vstřícný přístup, ochotu, čas a především trpělivost, kterou mi věnovala. Dále také mému konzultantovi a mentorovi MSc. Marcovi Minoia, Ph.D. za neocenitelné rady, podporu a neutuchající nadšení pro vědu. Poděkování rovněž patří celému týmu na VFU za vstřícné přijetí, jejich humor, pomoc a čas mně věnovaný. V neposlední řadě velké díky patří mé rodině za jejich podporu, a to především mé milující manželce Barboře, která z každé strasti dokáže vykouzlit procházku růžovým sadem.

Prohlášení

Prohlašuji, že jsem svoji diplomovou práci vypracoval samostatně s využitím informačních zdrojů, které jsou v práci citovány.

Brno 10. května 2018 Tomáš Nohejl

Table of Contents

1. Introduction ...... 11 1.1 Dissemination of antibiotic resistance by horizontal gene transfer ...... 12 1.1.1 Mechanism of horizontal gene transfer in bacteria ...... 12 1.2 Mobile genetic elements in the dissemination of antimicrobial resistance ...... 16 1.2.1 Transposons ...... 17 1.2.2 Integrons and gene cassettes ...... 18 1.2.3 Plasmids ...... 18 1.3 Plasmid properties and characteristics ...... 19 1.3.1 Plasmid features ...... 19 1.3.2 Plasmid classification ...... 22 1.3.3 IncX plasmids ...... 23 1.3.4 Conjugative plasmids ...... 24 1.4 Plasmid fitness cost, stability and impact on the host bacteria ...... 26 1.5 Principles of antibiotic resistance in bacteria ...... 27 1.5.1 Antibiotics ...... 27 1.5.2 Antibiotic resistance ...... 28 1.5.3 Quinolones and resistance mechanisms in bacteria ...... 29 2. Goals ...... 31 3. Material ...... 32 3.1 Microorganisms ...... 32 3.2 Plasmids ...... 33 3.3 Culture media ...... 34 3.4 Devices ...... 35 3.5 Chemicals ...... 36 3.5.1 Chemicals for polymerase chain reaction (PCR) and gel electrophoresis ...... 36 3.5.2 Antimicrobials ...... 36 3.5.3 Commercial kits ...... 37 3.5.4 Other chemicals ...... 37 3.6 Other equipment ...... 37 4. Methods ...... 38 4.1 Transformation ...... 38 4.2 Plasmid detection ...... 38 4.2.1 Polymerase chain reaction with specific primers ...... 38 4.2.2 Agarose gel electrophoresis ...... 40

4.3 Conjugation experiment ...... 40 4.3.1 Selection of suitable antibiotic resistant recipient cells...... 40 4.3.2 Conjugation ...... 41 4.4 Fitness cost experiment ...... 43 4.4.1 Manual spectrophotometer method ...... 43 4.4.2 Automated spectrophotometer method using Tecan ...... 43 4.5 Persistence experiment ...... 44 5. Results ...... 45 5.1 Plasmid detection after transformation ...... 45 5.2 Selection of representative plasmids for each IncX group ...... 46 5.2.1 Fitness cost of IncX plasmids via manual spectrophotometer method ...... 46 5.2.2 Fitness cost of IncX plasmids via automated spectrophotometer method ...... 48 5.3 Conjugation experiment ...... 51 5.3.1 Frequency of plasmid transfer ...... 52 5.4 Fitness cost of IncX plasmids related to host background and cultivation media ... 56 5.5 Persistence experiment ...... 59 6. Discussion ...... 60 7. Conclusion ...... 65 8. References ...... 66 9. Appendices ...... 74 10. List of abbreviations ...... 77

1. Introduction

The continuous spread of antibiotic resistance combined with the lack of new antibiotics in the production pipeline represents one of the world's most pressing public health problems. Recent data generated by the European Centre for Disease Prevention and Control (ECDC) estimated that infections due to multidrug-resistant bacteria cost to health care systems approximately €1,5 billion per year as a consequence of increased length of hospitalization (> 2,5 million extra hospital days) and increased mortality (25 000 people per year) (European Centre for Disease Prevention and Control 2009). A large amount of these costs is due to infections caused by Escherichia coli and Klebsiella pneumoniae resistant to second-generation fluoroquinolones through expression of plasmid-mediated quinolone resistance genes (PMQR), mainly of qnrS and qnrB. Further, in the last decades many big pharmaceutical companies exit the antibacterial drug discovery market. At present, most of the companies that remain in the antibiotic field continue to focus on new treatment for MRSA and related Gram-positive bacteria. Consequently, new treatments for Gram-negative infections may be more than a decade away.

It is well known that Horizontal Gene transfer (HGT) of mobile genetic elements (MGEs) play a major role in the spread of antibiotic resistance and the genes responsible for their transfer have been characterized (Snustad and Simmons 2009). The aim of this master project is to understand the relationship between stability of resistance plasmid and its burden on the cell fitness in context of dissemination of antibiotic resistance.

The environmental and genetic factors that regulate conjugative transfer of MGEs carrying antibiotic resistance genes are largely unknown. The effects of host internal environment on the regulation of HGT have only been studied in few MGEs of limited clinical interest (Bañuelos- Vazquez et al. 2017).

The hypothesis of this master thesis is that mobile genetic elements, and plasmids in particular, are highly adapted and integrated parts of the host bacteria and that expression of both plasmid and bacterial genes are important in the spread of resistance.

Dissemination of antibiotic resistance by horizontal gene transfer

One of the most interesting, and in certain aspects, surprising discoveries in the genome era is the evidence that prokaryotic genomes, and in some case also eukaryotic ones, carry significant amounts of DNA that was clearly obtained from other species (Soucy et al. 2015). These discoveries make it clear that Horizontal or Lateral Gene Transfer (HGT) has been much more common than previously appreciated. Indeed, at present time, HGT has found a mechanistic place next to point mutations and DNA rearrangements as the main sources for bacterial genome innovation and evolution.

Mechanism of horizontal gene transfer in bacteria

HGT is known to occur via three basic mechanisms: transformation, transduction and conjugation as seen in Figure 1 (Gyles and Boerlin 2014).

Figure 1. Mechanisms of DNA transfer within bacteria - Transduction (A); Conjugation (B) - plasmid integration into the chromosome (1, 3), plasmid remains independent (2), exchange of transposable elements between different plasmids (4); Transformation (C) (Gyles a Boerlin 2014, modified)

Transformation

Transformation refers to the uptake of free exogenous DNA present in the environment and is a natural feature of certain bacterial species, like Bacillus subtilis (Vojcic et al. 2012), Acinetobacter sp. (de Vries and Wackernagel 2002) or Vibrio cholerae (Seitz and Blokesch 2013). For other species, transformation is a state that can be forced by chemical or physical pretreatment of the cells. Transformation has been demonstrated even of plant-released DNA and rhizosphere bacteria (Richter and Smalla 2007), and also bacteria in the gastrointestinal tract have been shown to take up free DNA (Lerner et al. 2017). Most of the bacterial species that are spontaneously transformable have developed a system that allows them to enter in a “competent state”, but usually only during a certain period of their growth cycle (Blokesch 2016). This genetic competence can thus be considered a transient physiological state, the development of which is highly regulated by specific processes, including quorum sensing and nutritional signals. The transport of DNA into the cell is a complex mechanism that can be quite different between Gram-positive and Gram-negative bacteria, because of their different cell wall structure. Only one strand of DNA is physically transported into the cell while the other is degraded (Snustad and Simmons 2009). Usually a type IV pili (T4P) or a type II secretion system (T2SSs) are involved in the DNA uptake coupled with a DNA translocation complex (Ayers et al. 2010). DNA that is taken up by the cell can be fixed in the genome via recombination. Other authors assume that DNA transformation may serve a role in provision of nutrients for the cell (Sun et al. 2013).

Representative examples of successful transformation in context of antibiotic resistance is methicillin resistance in Staphylococcus aureus (Morikawa et al. 2012) or tetracycline resistance in Veillonella dispar (Hannan et al. 2010). Transformation also plays an important role in the spread of antibiotic resistance in Campylobacter jejuni (Bae et al. 2014) or Acinetobacter baylyi (Domingues et al. 2012). These DNA transformations usually occur in strict conditions such as in biofilms or in aquatic environment with extremely high bacterial concentration.

Transduction

In contrast to uptake of naked DNA, transduction implies packaging of host DNA into a viral (phage) capsid and subsequent transmission via renewed infection and integration or recombination. Most frequently, during phage-induced lysis of a host cell, phage nucleic acids are packaged into new phage capsids, but in rare events DNA from the host may become packaged as well and, in this form, it can transfer to a new cell. Transduction can occur in two different ways that have been named “generalized” or “specialized”.

Generalized transduction can occur when by chance during the lytic cycle of infection, bacterial chromosomal DNA is inserted into the viral capsid either instead of or in addition to viral DNA. Viruses that package the virion “headful” may accidentally fill their nucleocapsid with genetic material from the host and this can lead to the incorporation of bacterial DNA into the new virion. Upon renewed infection of another bacterial cell by the virus particle carrying the fragments of bacterial DNA, this can become reinserted and fixed in the genome via recombination.

Specialized transduction is defined as a result of mistakes in the excision process during transition from lysogenic to lytic cycle of integrated phages. In some cases, the phage DNA incorrectly excises itself from the bacterial chromosome, taking with it a fragment of bacterial DNA which is packaged in the phage capsid upon lysis. This phage-bacteria hybrid DNA can become injected into a new host cell and may integrated into the genome via recombination (Snustad and Simmons 2009).

Representative example of successful transduction in context of antibiotic resistance is the transfer of bacteriophages from E. coli carrying genes for antibiotic multiresistance in chicken meat (Shousha et al. 2015). Bacteriophages can also transfer tetracycline resistance from Enterococcus gallinarum to Enterococcus faecalis (Fard et al. 2011) or quinolone resistance genes (qnrA and qnrS) in the environment of wastewaters (Colomer-Lluch et al. 2014).

Conjugation

Finally, conjugation is the process characterized by a cell-to-cell exchange of genetic material between a donor and a recipient cell. It is mediated via a specifically formed pore or a pilus in conjunction to a DNA processing complex. Conjugative transfer is the outcome of a collection of different processes that start with the synthesis of a mating pair formation structure (Mpf) on the cell surface (Bañuelos-Vazquez et al. 2017). This step is fundamental to create a physical junction between the donor and recipient cell. Secondly, the DNA is prepared for the transfer by a protein machinery named the relaxosome. Despite much detailed work on a number of model systems, still a limited picture exists on this part of the conjugative mechanism. The relaxosome is thought to be composed of a relaxase/helicase and other proteins that bind to the DNA at the level of the origin of transfer (oriT). A single-strand break is produced on the DNA that has to be conjugated, which is then unwound to form single strand DNA (ssDNA). ssDNA is protected by a single-strand binding protein (Ssb), and the relaxosome is hypothesized to “present” the DNA to the Mpf with the help of “coupling proteins”, from where it is “pumped” into the new recipient cell. Experimental evidence suggests that the relaxase remains attached to the ssDNA even during and after transfer. Once in the recipient cell the relaxase helps recircularization of the transferred DNA (Lucas et al. 2010). For Gram-negatives the Mpf and the coupling proteins constitute what is called a type IV secretion system (T4SS). Even if the steps of DNA preparation are quite similar among different MGEs the transfer system can vary a lot, in particular concerning the architecture (Christie et al. 2014).

Despite similar outcome there are major differences between conjugation among Gram- negative and Gram-positive bacteria, particularly in the mechanisms that have evolved by which cell-cell contact is established to initiate the transfer. Gram-positive donor bacteria hereto produce adhesins that cause them to aggregate with recipient cells, but sex pili (mating pair proteins), the hallmark of Gram-negative conjugation, are not involved. Still, certain components of type IV secretion systems have been detected in Gram-positive conjugation systems, and this has been basis to hypothesize that conjugative DNA/protein transport in Gram-negative and Gram-positive bacteria have a common evolutionary origin (Grohmann et al. 2018).

Mobile genetic elements in the dissemination of antimicrobial resistance

MGEs comprise a wide variety of DNA segments encoding enzymes and other proteins that mediate the movement of DNA within (intracellular mobility) or between (intercellular mobility) genomes. MGEs include various types of integrative and conjugative elements such as integrons, insertion sequences, genomic islands, transposons, bacteriophages and plasmids. The acquisition and dissemination of antibiotic resistance by horizontal transfer follows a Chinese-box scheme as seen in Figure 2. A detailed look at the MGEs mediating antibiotic resistance has revealed that there are predominant clones that may contain predominant plasmids, which in turn contain predominant integrative elements (transposons, integrons, etc.) in which antibiotic resistance genes are enclosed (Johnson and Grossman 2015). It is largely known that resistance genes are often located on MGEs and many of them are well characterized. However, little is known about the mechanisms regulating transfer of these elements. In this section some of the MGEs will be described, in particular those that mediate resistance to antibiotics. Special attention will be paid to plasmids as the most important MGEs driving the dissemination of antibiotic resistance genes.

Figure 2. Hierarchal composition of mobile genetic elements (Norman et al. 2009, modified)

Transposons

Transposable elements or transposons (Tn) are able to move within and between chromosomes and plasmids. Transposons present in bacteria are divided based on their transposition mechanism into i) cut-and-paste transposons, which include insertion sequences and composite transposons, and into ii) replicative transposons represented by Tn3 elements (Snustad and Simmons 2009).

1.2.1.1 Insertion sequences

Insertion sequences (IS) are the smallest MGEs. As they have a maximum size of 2,5 kbp they carry only genes needed for the regulation of their self-transposition. Every element is defined by two short identical sequences at its ends. These flanking sequences are mutually inversely oriented and therefore they are called terminal inverted repeats. They play an important role in the ability of the transposon to move from one place in the genome to another one (Mahillon and Chandler 1998).

The most important protein involved in IS mobility is called transposase. This enzyme cuts both of the DNA strands at the ends of the IS element and enables its movement. Using this mechanism, the IS can be integrated to another location within the genome of the host cell. It is well known that IS directly contribute to genetic variability of bacteria that is, beside point mutations, one of the foundations of evolutionary changes in bacterial populations (Snustad and Simmons 2009).

1.2.1.2 Composite transposons

Composite transposons also belong to the cut-and-paste transposons family. They are composed of two insertion sequences (IS) integrated closely to each other and a variable DNA sequence located between them. The whole structure is transferable with the help of transposase produced by the IS. Common examples of composite transposons carrying antibiotic resistance genes are Tn5 (with IS50L and IS50R at the boundaries and genes for resistance to kanamycin, bleomycin and streptomycin), Tn9 (with two IS1 and chloramphenicol resistance genes) and Tn10 (flanked by IS10L and IS10R and carrying tetracycline resistance genes) (Snustad and Simmons 2009).

1.2.1.3 Replicative transposons

Replicative transposons are structurally very similar to composite transposons except for the structure of their ends where they contain 38 - 40 bp terminal inverted repeats. The most widespread transposon in prokaryotic cells is Tn3. This transposon carry genes for transposase (tnpA), resolvase (tnpR) and a bla gene coding for the enzymes called β-lactamases responsible for resistance to β-lactam antibiotics (Heffron et al. 1979).

Integrons and gene cassettes

Integrons are effective tools able to merge and integrate exogenous open reading frames (ORFs) and convert them into the functional genes by site-specific recombination. Fundamental parts of every integron are: a gene responsible for expression of tyrosine-recombinase family enzyme - integrase (intI); a promoter (Pc) initiating transcription of integron-encoded genes; and a primary recombination site (attI) (Mazel 2006).

Gene cassette contain and a recombination site (attC) and usually encode resistance to antibiotics. They occur in a form of free circular DNA or they are captured and incorporated into integrons within bacterial plasmid and chromosome. Recombination between attI and attC sites enables integration or excision of gene cassettes into the integrin structure. Gene cassettes are unable of self-replication so they replicate and disseminate with the help of integrons (Partridge et al. 2009).

Plasmids

Plasmids are extrachromosomal, double stranded and most commonly circular DNA molecules within bacterial cells. They replicate independently on the bacterial chromosome, but they use host replicative machinery. Plasmids can be found in almost every bacteria and they have various sizes from 1 kbp to few hundreds of kbp (Dale and Park 2010). Most plasmids are not essential for survival of the host cell but they may play an important role in the ecology and adaptation of the bacteria (Shintani et al. 2015).

Because plasmids are of crucial importance for the dissemination of antibiotic resistance genes (Bennett 2008) and they are the main focus of this thesis, they will be analysed in more details in section 1.3 Plasmid properties and characteristics.

Plasmid properties and characteristics

Many different types of elements have been implicated in DNA mobility in general. Of particular interest to this thesis are plasmids, which mostly have been discovered many years ago, but more recently genome sequencing and genome-to-genome comparisons have put new lights on their features and their importance in gene dissemination.

Plasmids significantly influence the elementary biological properties of their bacterial host. They play a major part in the host diversity and evolution. Plasmids are used for the study of fundamental molecular processes within the cell or even for the genetic engineering as vectors (Snustad and Simmons 2009).

Plasmid features

Plasmids can be defined as a discrete circular fragment of DNA present in a prokaryotic host, but with a distinct sequence signature or motive different from the host chromosome (Shintani et al. 2015). Below are listed the current features that are used to exemplify a plasmid.

1.3.1.1 Plasmid replication

The most crucial part of every plasmid is its replication mechanism needed for the survival of the DNA molecules within the bacteria. The specific sequence called origin of vegetative replication (oriV) is composed of iterons and segments rich for adenosine and tyrosine (Funnell and Phillips 2004). Iterons and replication initiator proteins (Rep) are essential initiator parts of plasmid replication. The RepA protein is able to initiate or inhibit replication or act as a transcription self-repressor. Short DNA sequences called iterons serve as Rep protein binding sites on plasmids (del Solar et al. 1998).

There are two paths of vegetative plasmid replication. Theta (θ) replication used by circular plasmids of Gram-negative bacteria, initiates at the oriV and continues bidirectionally. The second path is the rolling circle replication that starts by nicking one strand of the plasmid DNA on its 3′-OH end and continues with the strand displacement along the circular plasmid DNA (del Solar et al. 1998).

1.3.1.2 Plasmid transfer

The most intriguing plasmid ability is horizontal gene transfer. Transfer (Tra) operon is a region with tra genes encoding proteins needed for successful transfer of DNA segment. Plasmid transfer mechanism consists of two essential elements: the transferosome and relaxosome.

The transferosome is a protein complex forming a pore in the cell transmembrane. This pore allows the transfer of the DNA. Meanwhile the relaxosome composes of proteins mediating plasmid conjugation encoded by Tra operon. The uppermost protein of relaxosome is relaxase that initiates plasmid transfer at the oriT and unwinds the plasmid DNA. (Wong et al. 2012; Godziszewska et al. 2014).

1.3.1.3 Plasmid stability

According to the copy number, plasmids can be divided into larger low-copy (1 - 10), medium-copy (10 - 20) and smaller high-copy (20>) molecules. The frequency of a plasmid replication directly correlates with its copy number within the cell. Mutations in the ori sequence may influence the plasmid copy number. Therefore, their classification into groups based on plasmid counting is not sufficiently reliable, while classification by plasmid replication mechanism is more accurate (Friehs 2004).

The plasmid persistence in the host cell (also known as plasmid stability) during the cell division is provided by a plasmid partition (Par) system. This system is of extreme importance for plasmid stability, especially for the persistence of low copy plasmids. The Par system works similarly as the segregation system for bacterial chromosome and involves two Par proteins and a DNA site. In general, the first Par protein (ParB, SopB, RepB, etc.) binds to centromere-like DNA on the plasmid and the second protein (ParA, SopA, RepA, etc.) works as an ATPase that is essential for movement of ParB-DNA complex. The plasmid emplacement ensures the equal plasmid distribution to the daughter cells as seen in Figure 3 (Funnell and Phillips 2004). The plasmid loss is caused by changes in the plasmid structure responsible for regulation or expression of proteins (Friehs 2004).

The high-copy plasmids lack partition systems and rely on high number of their copies present in the cell to avoid their loss during segregation. The difference between low-copy and high-copy plasmids partition strategy can be seen in Figure 3 (Slonczewski and Foster 2013). The burden of either low-copy or high-copy plasmids for the host cell is similar but the

20 persistence of the plasmid in the host cell may differ (San Millan et al. 2014). See chapter 1.4 Plasmid fitness cost, stability and impact on the host bacteria.

Figure 3. Partitioning of high-copy (A) and low-copy (B) plasmids (Slonczewski and Foster 2013)

1.3.1.4 Plasmid addiction systems

Even though plasmids have quite efficient stability systems they also have the need for an addiction strategy that further prevents dividing cells from losing the plasmid. Typically, such systems are known as toxin/antitoxin (TA) systems and are very widespread among plasmids (Rankin et al. 2012).

Bacterial TA systems can be mainly divided in two big families depending on the nature of the antitoxin they carry. In the first group (type I), the antitoxin is a small RNA that inhibits toxin translation (Berghoff and Wagner 2017), while the toxins are small hydrophobic proteins that damage cellular membranes. Type II systems involve a small unstable antitoxin protein that inhibits the toxin forming a protein complex with it (Rocker and Meinhart 2016). The latter is probably the most diffused amongst plasmids.

When plasmid is retained in the host both the toxin and the antitoxin are present simultaneously allowing the survival of the host cell itself. As the half-life of the toxin is longer

21 than the one of the antitoxin, when the plasmid is lost the host runs low on antitoxin very quickly, resulting in a fast cell death due to the toxin activity (Funnell and Phillips 2004).

Plasmid classification

Plasmids can be classified by their function, incompatibility or their ability to be transferred between bacterial cells.

1.3.2.1 Plasmid classification by function

Plasmids can carry several different traits that can grant various capabilities to the bacterial host. Therefore, based on carried functions, plasmids can be classified into different functional groups. However, a pitfall of this strategy is that a single plasmid can fall into multiple groups if it carries genes for distinct functions.

Following the division based on functionality, the first plasmid group that will be described is the group of the fertility plasmids (F-factors). These plasmids carry genes required for the horizontal transfer via conjugation and they may be integrated into the bacterial chromosome via specific recombination when they share the same short DNA sequences in their structure. Bacteria with the chromosomally integrated F-factor are called high-frequency recombination cells (Hfr cell). In case of the Hfr cells, the F-factor can also transfer the bacterial chromosome itself. The cells usually separate before completion of the transfer of the whole chromosome resulting in only partial exchange of chromosomal genes (Snustad and Simmons 2009).

The second functional group includes resistance plasmids (R-plasmids) which are responsible for antibiotic resistance of the bacteria. They provide a certain fitness advantage for the host cells in the hostile environment of antibiotics and other antibacterial agents like heavy metals (MacLean and San Millan 2015). Plasmids carrying multiple genes conferring resistance to several different antibiotics are termed as multidrug-resistance (MDR) (Dale and Park 2010). Resistance genes carried by plasmids are located on the integrated MGEs such as transposons, integrons or gene cassettes. This composition simplifies the transfer of antibiotic resistance genes between different MGEs or even between a MGE and chromosome (Norman et al. 2009). Because R-plasmids usually have the ability to be transferred via conjugation to other cells, they are the perfect tool for bacteria to expand an efficient defensive system against antimicrobials. This fact makes them the topmost priority for study (Carattoli 2009).

The third group encompass the colicinogenic plasmids (Col plasmids) carrying genes for bacteriocins that are peptidic toxins with the ability to kill other bacterial cells or to inhibit their growth. They are named after the first discovered Col plasmid encoding colicine. Colicine is a toxin (“coli-killer”) that kills the sensitive E. coli (Watson et al. 1981).

The fourth group includes degradative plasmids. Usually belonging to the P incompatibility group, they are widespread in Pseudomonas spp. They are able to catabolize chemical compounds in the environment. One of the most studied member of this group is the Tol plasmid coding enzymes for toluene degradation (Shintani et al. 2010). Degradative plasmids can often carry entire or even multiple degradation pathways composed by many different genes. This significantly increases the size of the plasmid (Funnell and Phillips 2004).

Finally, another significant functional group worth to be mentioned is the one composed by virulence plasmids that carry virulence genes coding enterotoxins. They are responsible for the pathogenicity of the bacteria causing disease in host organism (Funnell and Phillips 2004). Pathogenic bacteria interfere with the host immunity system and the vir genes also provide bacterial surface adhesion. These features increase the survivability of the cell in the hostile environment (Hicks and Rowbury 2008; Johnson and Nolan 2009).

1.3.2.2 Plasmid incompatibility

While classification by function may sometimes be misleading since one plasmid can provide several functions at once, incompatibility enables easy and reliable categorization of plasmids into groups. Plasmid incompatibility is an attribute of every plasmid. Two different plasmids belonging to the same incompatibility group cannot coexist simultaneously in one cell. Based on this definition, plasmids are divided into incompatibility (Inc) groups (Couturier et al. 1988). Plasmid are not compatible as the result of the similarity in replication mechanisms, especially by sharing elements like oriV or Par systems (Novick 1987). The major plasmid families spreading in bacteria of Enterobacteriaceae family were detected via PCR-based replicon typing (PBRT) and include A/C, B/O, FIA, FIB, FIC, HI1, HI2, I1-γ, K, L/M, N, P, T, W, X and Y incompatibility groups (Carattoli et al. 2005).

IncX plasmids

IncX plasmid family is predominantly found in members of Enterobacteriaceae and Pseudomonadaceae family in humans, wildlife, captive, domestic and food-producing animals and the environment (Carattoli 2013; Dobiasova and Dolejska 2016). 23

Plasmid of this group have a conservative backbone consisting of regions for conjugation, replication, partitioning and toxin/antitoxin system (Norman et al. 2008). The fundamental genes of the IncX backbone are pir, bis (replication), par (partitioning), hns (DNA- binding), topB (topoisomerase), pilX (pilus), actX (transcription), taxC (DNA transfer relaxase) and taxA (DNA transfer auxiliary protein) (Norman et al. 2008; Johnson et al. 2012). IncX plasmids has been divided into seven subgroups which differ from each other mostly by nucleotide sequence of taxC gene coding for DNA transfer relaxase (Johnson et al. 2012). The size of these plasmids vary from 30 to 80 kbp (Li et al. 2018).

IncX plasmids often carry antibiotic resistance genes including those for resistance to the most important antimicrobial agents of current medicine. They are associated with determinants for resistance to fluoroquinolones that are called plasmid-mediated quinolone resistance (PMQR) genes (Rodríguez-Martínez et al. 2016). PMQR genes are often accompanied by genes mediating resistance to cephalosporins, carbapenems, colistin and other antibiotics (Guo et al. 2017).

Conjugative plasmids

Plasmids containing Tra region can be transferred between cells via conjugation and they are called conjugative plasmids. Conjugative plasmids, which are usually > 20 kbp in size, are the key contributors to the horizontal gene transfer (Smillie et al. 2010). An integral part of every conjugative plasmid is the oriT together with the complete protein machinery for conjugative transfer (Garcillán-Barcia et al. 2009).

The structure of a conjugative plasmid is divided into several regions with genes responsible for: i) plasmid replication with segment maintaining stable copy numbers (cop); ii) plasmid dissemination by conjugative transfer; and iii) plasmid stability via partitioning. These regions are needed for the plasmid survival and altogether form a conservative structure termed plasmid backbone (Norman et al. 2009). There is a forth region containing genes encoding beneficial traits for the host such as resistance to antibiotics as seen in conjugative R-plasmids.

Conjugative R-plasmids are composed of backbone called resistance transfer factor (RTF) and variable region called R-determinant with genes responsible for resistance to antibiotics. These genes are often located on transposons integrated into the plasmids as seen in Figure 4. Conjugative plasmids are transferred rapidly even between distantly related cell types resulting in wide spread of antibiotic resistance (Snustad and Simmons 2009).

Figure 4. Formation of conjugative R-plasmid. The figure demonstrates recombination event between IS1 elements on nonconjugative and conjugative plasmid that results in formation of conjugative plasmid with resistance to streptomycin (strr) (Snustad and Simmons 2009, modified)

Plasmid fitness cost, stability and impact on the host bacteria

MGEs usually pose a burden on their hosts because of additional genes needed for their functions (Vogwill and MacLean 2015). The burden can for example result in a slower growth rate. Indeed, in an environment without antibiotic selection pressure, the wild type bacteria tend to overcome growth rates of antibiotic resistant strains (Andersson and Hughes 2010).

When a cell acquires a new plasmid it usually undergoes to a series of compensatory mutations that should help the host to “compensate” for the additional burden caused by the newly acquired plasmid. For example, these mutations can at least partially restore the original growth rate of the host cells without effecting the resistance mechanism. Indeed, compensatory mutations that involve the complete loss of antibiotic resistance are extremely rare. These findings led to the implication that lowering the use of antibiotics may not lead to the final solution of the antibiotic crisis (Björkman et al. 2000) and challenge the common assumption that plasmids persist in the host bacteria only if there are need for of the host’s survival. According to this idea, giving the burden caused to the host, the plasmid should be lost rapidly when antibiotic resistance is not required (Cottell et al. 2012).

The recent knowledge leads to the idea that plasmids persist in host cells for a long period of time even in the antimicrobial-free environment. However, the mechanism of plasmid persistence has not yet been fully elucidated, although it is assumed that the toxin/antitoxin system and compensatory adaptation by chromosomal and/or plasmid mutations are some of the reasons behind the plasmid persistence (Funnell and Phillips 2004; Carroll and Wong 2018).

Principles of antibiotic resistance in bacteria

Antibiotics

The antibiotics, also known as antibacterial agents, are chemical substances that negatively interfere with the bacteria. They are used to treat and prevent bacterial infections. Antibiotics can be divided into two main distinct categories: i) bacteriostatic antibiotics that are inhibiting bacterial growth and replication, and ii) bactericidal molecules causing the death of bacterial cell. Antibiotic families are then identified based on their chemical structure, mechanism or spectrum of action (Schwalbe et al. 2007). Antibiotics target different essential structures of the bacterial cell and their function as seen in Figure 5 and Table 1 (Wright 2010). Figure 5. Antibiotic targets (Wright 2010, modified)

Table 1. Antibiotic modes of action

Mode of action Examples of antibiotics Inhibition of cell wall synthesis β-lactams, Bacitracin, Vancomycin Inhibition of cell membrane function Colistine, Daptomycin, Polymixin B Aminoglycosides, Chloramphenicol, Linezolid, Inhibition of protein synthesis Macrolides, Tetracyclines Inhibition of nucleic acid synthesis Fluoroquinolones, Rifampicin Inhibition of other metabolic processes Sulfonamides, Trimethoprim

Antibiotic resistance

Antibiotic resistance is a cell protective mechanism that increases cell survival in the environment with damaging antibiotic. Antibiotic resistance in bacteria has evolved over time due to selective pressure of antibacterial agents. Now we are entering an era of antibiotic resistance crisis when many bacterial infections are no longer treatable by known antibiotics (Gould and Bal 2013).

Antibiotic resistance in bacteria is escalated by overuse of antibiotics, incorrect disease diagnosis and consequently with an inappropriate drug prescription. The major role in increasing trends of antibiotic resistance is also played by antibiotics used in animal production. They are used for treating infection outbreaks, but also as precaution from pathogen spread or promotion of animal growth. Treating animals with a non-lethal dose of antibiotics results in selection of resistant bacteria. These misuse creates a constant selection pressure and allows further evolution and dissemination of the antibiotic resistance (Barriere 2015).

The nature of antibiotic resistance depends on genes that mediate it. Mechanism of bacterial resistance to antibiotics occurs in four general ways - target-site modification, efflux pumps emitting pathogens from the cell, enzymes inactivating antibiotic functions or circumventing inhibition as seen in Figure 6 (Wright 2010).

Resistance to one type of antibiotic can be achieved by diverse ways at once. Bacteria can use multiple resistance mechanisms to overcome the antibiotic effect (Munita and Arias 2016).

Figure 6. Mechanisms of antibiotic resistance (Wright 2010, modified)

Quinolones and resistance mechanisms in bacteria

Quinolone antibiotics are one of the most significant antibiotic groups due to their broad-spectrum efficacy against bacterial pathogens in both human and veterinary medicine. An increase in quinolone consumption has led to a rapid increase of bacteria resistant to this group of antibiotics (Aldred et al. 2014).

1.5.3.1 Quinolones – structure and mode of action

Quinolones are synthetic antibiotics with the structure built on bicyclic molecule. The first antibiotic from this group was nalidixic acid discovered in 1962 and clinically used since 1967. The following spread of the antibiotic resistance to nalidixic acid lead to the development of novel and more successful quinolone antibiotics. The first significant improvement was introduced in 1976 by quinolone antibiotic, flumequine, with fluorine atom in its chemical structure. The group of quinolone antibiotic with fluorine atom was later termed fluoroquinolones and are broadly used in human and veterinary medicine since then. They are used to treat various infections cause by Gram-negative bacteria (Emmerson 2003).

At appropriate fluoroquinolone dosage, quinolones are bactericidal. They target DNA synthesis machinery by their binding to gyrase or topoisomerase IV, leading to a formation of a complex with DNA. This complex results in inhibition of relaxing DNA supercoils and therefore rapid inhibition of DNA replication (Brighty and Gootz 2000; Hawkey 2003).

1.5.3.2 Mechanisms of bacterial resistance to fluoroquinolones

Resistance to fluoroquinolones is mediated mainly by two separate ways which are chromosome-mediated and plasmid-encoded. There is also a third way of obtaining resistance to fluoroquinolones, and that is by downregulation of the influx channel proteins. However, the third mechanism provides only minor resistance, so the following chapters are focused on the main two ways.

Chromosomal quinolone resistance

Resistance to quinolones associated with the bacterial chromosome is enabled by target- site mutations. These mutations occur in genes encoding DNA gyrase and topoisomerase IV, resulting in the reduction of the ability of fluoroquinolones to bind to the enzymes with modified structure. That results in the decrease of fluoroquinolone ability to inhibit DNA ligation (Aldred et al. 2014). In Gram-negative bacteria, mutations reducing antibiotic affinity 29 occur in a quinolone-resistance-determining region (QRDR) of genes encoding GyrA subunit of DNA gyrase. In case of Gram-positive bacteria, mutations occur within the QRDR for ParC subunit of topoisomerase IV. Combination of mutations in both regions significantly increases the antibiotic resistance of the cell (Silva-Sánchez et al. 2013; Kim and Hooper 2014).

Plasmid-mediated quinolone resistance

Plasmid-mediated quinolone resistance (PMQR) is transmissible quinolone-resistance mechanism and is associated with the presence of genes encoding three different resistance mechanisms based on DNA protection, enzymatic inactivation and the efflux of the antibiotic (Jacoby et al. 2014).

The qnr family, including qnrA, qnrS, qnrB, qnrC, qnrD and other less frequent genes, encode Qnr proteins that bind to DNA gyrase and topoisomerase IV and protect them from inhibition mediated by quinolones (Rodríguez-Martínez et al. 2016). Qnr proteins usually provide a low level of resistance but this opens an opportunity for further selection for additional resistance mutations in gyrA or other related genes, resulting in resistance to high concentration of the antibiotic (Jacoby 2005). The qnr genes can be found in multiresistance plasmids often along with β-lactamase genes or other resistance determinants (Jacoby et al. 2014).

Another group of resistance mechanisms is represented by aac(6′)-Ib-cr gene that encodes an acetylating enzyme degrading fluoroquinolones within the cell (Redgrave et al. 2014). These genes can be found worldwide in Enterobacteriaceae and Pseudomonas aeruginosa. The Aac(6′)-Ib-cr enzyme has two amino acid substitutions (Trp102Arg and Asp179Tyr) and is able to acetylate quinolones, specifically their amino nitrogen. It is commonly found within integrons in a form of gene cassette and carried by multiresistance plasmids (Jacoby et al. 2014).

Another family of PMQR genes includes qepA or oqxAB. These genes encode efflux pump systems able to actively export fluoroquinolones out of the cell (Redgrave et al. 2014; Rodríguez-Martínez et al. 2016).

2. Goals

Main goals of the thesis are summarized in the following points:

• Transformation of IncX plasmids carrying qnr genes into chemically competent E. coli cells • Frequency of conjugative transfer of IncX plasmids into various recipient cells including laboratory and wildtype pathogenic strains of several species • Fitness cost of IncX plasmids for host bacteria of several species carrying these plasmids • Stability of representative IncX plasmids in host cells without antibiotic selective pressure

3. Material

The following section summarizes the material used for experimental part of the thesis performed in the laboratory.

Microorganisms

All microorganisms used as recipients either for transformation or conjugation as well as for further experiments were plasmid-free bacteria from families Enterobacteriaceae and Pseudomonadaceae. For detailed information of the strain characteristics see Table 2.

Table 2. List of used bacterial strains

Bacterial strain Reference Pathogenicity Resistance* Use**

Escherichia coli InvitrogenTM, USA Laboratory strain - C, F, P, T TOP10

Assoc. Prof. Hrabak, Faculty of Medicine in Escherichia coli A15 Pilsen, Charles Laboratory strain AzidR C, F, P University, Czech Republic

Uropathogenic Dept. of Clinical Escherichia coli 536 Science, University of Pathogenic strain RifR C, F, P (UPEC536) Bergen

Escherichia coli ST131 (Albrechtova et al. 2012) Pathogenic strain RifR C, F, P

National Institute of Salmonella enteritidis Public Health, Czech Pathogenic strain AzidR, RifR C, F, P FA-8065 Republic Assoc. Prof. Hrabak, Faculty of Medicine in Pseudomonas Pilsen, Charles Pathogenic strain StrR C, F, P aeruginosa 481/02 University, Czech Republic *AzidR - Azide resistance with minimal inhibitory concentration (MIC) of 100 mg/l; RifR - Rifampicin resistance with MIC of 50 mg/l; StrR - Streptomycin resistance with MIC of 25 mg/l.

**C - Conjugation experiment; F - Fitness cost experiment; P - Persistence experiment; T - Chemically competent cells for transformation of plasmid DNA.

Plasmids

All used plasmids belong to the IncX group and were found in wildtype E. coli isolates of various origins, including wildlife, wastewater and a companion animal. Plasmid characteristics such as size, Inc subgroup and content of antibiotic resistance genes are summarized in Table 3.

Table 3. List and characteristics of used IncX plasmids

Antibiotic resistance genes in the Plasmid Inc Size (bp) Origin of the isolate* isolate

pHP2 X1 47,686 Wild bird - CZ qnrS1, blaTEM-1

pCE780h4 X1 60,848 Wastewater - CZ qnrS1, blaTEM-1, aadA1, floR

pCE1551 X1 56,600 Wild bird - AUS qnrS1, blaTEM-1, aadA1, floR, sul3 p194 X2 39,584 Wild bird - CZ qnrS1, tetA(A) p615cip X2 31,584 Domestic dog - SK qnrB19 pHP103 X2 35,056 Wild bird - CZ qnrS2

pHE40 X2 45,484 Wild bird - ES qnrS1, blaTEM-1, aadA2

pCE1594 X2 43,897 Wild bird - AUS qnrS1, blaTEM-176

p1456h8 X3 45,645 Wastewater - CZ qnrS1, blaSHV-12

pHD76 X3-N ~80,000 Wild bird - DE qnrS1, blaSHV-12, blaTEM-1 *AUS - Australia; CZ - Czech Republic; DE - Germany; ES - Spain; SK - Slovak Republic

IncX plasmids studied within this thesis carry PMQR genes, qnrS1, qnrS2 or qnrB19, coding for resistance to quinolones and they have been previously characterized by Dobiasova and Dolejska (2016). In that study, two plasmids from IncX1 (pHP2) and IncX2 (p194) were widespread among various E. coli genotypes originating from several sources and geographical locations. The complete sequencing of these plasmid has been obtained, however, this analysis has been conducted by Dolejska et al. (unpublished data) and was not part of my thesis. The sequence data were subsequently used in my work in order to choose suitable antibiotics for in vitro experiments. The structure of MDR region of the two representative IncX1 and IncX2 plasmids is showed in Figure 7 and complete pHP2 and p194 plasmid maps are included in section 9. Appendices. Plasmid pHP2 carried additional gene blaTEM-1 for ampicillin resistance while p194 contained tetracycline resistance gene tetA(A).

Figure 7. Model structure of pHP2 and p194 MDR plasmid region

Culture media

All culture media were prepared according to the producer’s instructions except the Minimal Medium (see below). Media were autoclaved before use and tempered in a bath at 50 °C.

• Brain heart infusion (BHI) broth (Oxoid, Great Britain) • LB agar (Sigma-Aldrich, USA) • Luria-Bertani medium/Lysogeny broth (LB) broth (BD Difco, USA) • Minimal Medium (MM) • M9 salts (1 l) autoclaved at 121 °C for 20 min.

• Na2HPO4 x 2H2O 7,52 g

• KH2PO4 3 g • NaCl 0,5 g

• NH4Cl 0,5 g

• 1M MgSO4

• 1M CaCl2

• 0,01M FeSO4 • Thiamine HCl 50mg/100ml (0,5g/l) • Leucine 23mM (0,3g/l) • Glucose 20% • Proline 23mM (0,3g/l)

• Preparation of 100 ml of MM: • M9 salts 100 ml

• MgSO4 200 µl

• CaCl2 1 µl

• FeSO4 100 µl • Thiamine 1 ml • Leucine 1 ml • Glucose 2 ml • Proline 1 ml

Devices

• Analytical laboratory balances AS 110.R2 (Radwag, Poland) • Autoclave Sterilab (BMT Medical Technology s.r.o., Czech Republic) • Biological safety cabinet - Safe 2020 (Thermo Fisher Scientific, USA) • Biometra Professional Trio Thermocycler (Analytik Jena, Germany) • BioPhotometer UV/Vis Spectrophotometer (Eppendorf, Germany) • Centrifuge Z326K (Hermle AG, Germany) • eCountTM Colony Counter Pen (Heathrow ScientificTM, USA) • EnduroTM power supply for electrophoresis 300V (LabNet, USA) • Eppendorf Easypet 3 (Eppendorf) • Eppendorf Multipette® M4 (Eppendorf) • Imaging device - MF-ChemiBIS 3.2 (Bioimaging Systems, Israel) • Incubator - Lab Companion IL-11 Low Temp Incubator (Jeiotech, South Korea) • Laboratory scales EK-200G (A&D, Japan) • Microcentrifuge miniSpin (Eppendorf) • Micropipettes (Eppendorf) • Microwave CMW 200S (Candy, Italy) • Optizen POP BIO (Mecasys, South Korea) • Refrigerated centrifuge 5415R (Eppendorf) • Refrigerators, Freezers • Shaking incubator 205L (N-BIOTEK, South Korea) • Shaking Water Bath NB-303 (N-BIOTEK), WB 14 (Memmert, Germany) 35

• Tecan Infinite® M200PRO (Tecan, Switzerland) • UV transilluminator - Vilber Lourmat TFX-20.M (Sigma-Aldrich) • Vortex V-1 plus (Biosan, Latvia)

Chemicals

Chemicals for polymerase chain reaction (PCR) and gel electrophoresis

• 100 bp DNA ladder, 100-1500 bp (BioLabs, Great Britain) • Distilled water • MIDORI (Nippon Genetics, Japan) • PCR-water (Top-Bio, Czech Republic) • PPP Master Mix (Top-Bio) • Primers (see Table 5) (Macrogen Europe, Netherlands) • Seakem LE agarose (Lonza, USA) • TBE buffer • 10×TBE buffer was prepared with 60,5 g of Tris-base (Sigma-Aldrich), 30,85 g of boric acid (Penta, Czech Republic) and 4,16 g of EDTA disodium dihydrate (Penta) dissolved in 1 l of distilled water. • The pH of the buffer was adjusted to 8,0 and then autoclaved at 121 °C for 20 min. • 1×TBE buffer was prepared by diluting the stock 10×TBE buffer.

Antimicrobials

• Ampicillin (stock solution of 100 mg/ml) • Ciprofloxacin (0,05 mg/ml) • Kanamycin (50 mg/ml) • Rifampicin (50 mg/ml) • Sodium azide (100 mg/ml) • Streptomycin (25 mg/ml) • Tetracycline (20 mg/ml)

Commercial kits

• PCR purification kit (Qiagen, Germany) • Plasmid DNA isolation Miniprep Kit (Qiagen)

Other chemicals

• Glycerine • Physiological solution - NaCl (Penta)

Other equipment

• Cryotubes CryoPure Tube 1,8ml (Sarstedt, Germany) • Cuvettes UVette® (Eppendorf) • Disposable gloves • Disposable serological pipets (Fisher Scientific, USA; Jet Biofil®, China) • Electrophoresis tank, trays, combs (Thermo Fisher Scientific) • Eppendorf Combitips advanced® (Eppendorf) • Eppendorf tubes (1,5ml, 200µl) (Eppendorf) • Laboratory glassware (FisherBrandTM, USA; SCHOTT DURAN®, Germany; Simax, Czech Republic) • Laboratory sealing film Parafilm® (Sigma-Aldrich) • Micropipette tips (AHN Biotechnologie, Germany; Capp, Denmark; Neptune, USA) • Microtiter plates (TPP, Switzerland) • Plastic Petri dishes with a diameter of 90 mm (Ligamen, Czech Republic) • Scissors, tweezers • Sterile conical tubes (50ml) (DispoLab, Czech Republic) • Sterile filters • Sterile plastic disposable cell spreaders (Biologix, USA) • Sterile plastic disposable loops (1µl) (Biologix) • Sterile urine tubes (10ml) (CC-CITO-CONT, Czech Republic) • Wooden picks

4. Methods

Transformation

Plasmid DNA were transferred to E. coli TOP10 competent via chemical transformation using a heat shock technique. Plasmid DNA was provided by the supervisor and the DNA extraction was not part of my work. A total of 50 µl of competent cells stored at -80°C was left to unfreeze in ice and then 500 ng of plasmid DNA was added. Mixture rested in ice for 20-30 minutes and then it was placed in thermoblock at 42 °C for 45-60 seconds. After the heat shock, the mix was kept in ice for 1-2 minutes and then transferred into a microtube containing 1 ml of LB broth. The mixture was then incubated for 1 hour in 37 °C while shaking (170 rpm). After the incubation, the mixture was centrifuged (5000 rpm for 2 minutes) in order to concentrate the cells and reduce the volume to 50 µl. This 50 µl was then pipetted on selective plates and dispersed on the surface of the media using cell spreaders. Plates were left incubating overnight at 37 °C.

Plasmid detection

The transfer of plasmid DNA into recipient cells using transformation was confirmed via polymerase chain reaction (PCR) of resistant colonies growing on selective media with antibiotics.

Polymerase chain reaction with specific primers

PCR mixes were prepared with Master Mix, PCR water and primers so that every sample had a total volume of 12 µl of PCR mix. Composition of PCR mix and the pipetted volumes are demonstrated in Table 4. The list of the primers including nucleotide sequences and target genes are shown in Table 5. After homogenization of the sample thoroughly on vortex, PCR mixture was pipetted into microtubes and 1 µl of bacterial DNA was added. PCR water was used instead of bacterial DNA as a negative control. Various bacterial strains were used as a positive control as mentioned in Table 6. All microtubes were placed into the thermocycler and PCR was initiated according to the PCR programme shown in Table 7.

Table 4. Composition of PCR mix with volumes for one sample

Component Volume per sample (µl)

Master Mix 6,25 PCR water 4,75

Forward primer 0,5

Reverse primer 0,5

Table 5. List of primers used for detection of qnr and IncX genes

Primer name Sequence (5'-3') Target gene Reference qnrB-F GAT CGT GAA AGC CAG AAA GG qnrB (Cattoir et al. 2007a) qnrB-R ATG AGC AAC GAT GCC TGG TA qnrS-F GCA AGT TCA TTG AAC AGG GT qnrS (Cattoir et al. 2007b) qnrS-R TCT AAA CCG TCG AGT TCG GCG IncX1-F GCT TAG ACT TTG TTT TAT CGT T IncX1 (Johnson et al. 2012) IncX1-R TAA TGA TCC TCA GCA TGT GAT IncX2-F GCG AAG AAA TCA AAG AAG CTA IncX2 (Johnson et al. 2012) IncX2-R TGT TGA ATG CCG TTC TTG TCC AG IncX3-F GTT TTC TCC ACG CCC TTG TTC A IncX3 (Johnson et al. 2012) IncX3-R CTT TGT GCT TGG CTA TCA TAA

Table 6. List of positive controls for PCR

Target gene Bacterial strain Reference qnrB19 E. coli qnrB19 Collection of microorganisms, Denmark qnrS1 E. coli qnrS1 Collection of microorganisms, Denmark IncX1 E. coli CE 279 e4 (Dobiasova and Dolejska 2016) IncX2 E. coli HPG 121 (Jamborova et al. 2015) IncX3 E. coli CE 1251 (Dobiasova and Dolejska 2016)

Table 7. PCR programme for specific amplification of qnrB, qnrS and IncX gene segments

Step Temperature (°C) Time 1 Initial denaturation of DNA 94 10 min 2 Denaturation of DNA 94 1 min 3 Primer annealing 52 45 s 4 Amplification 72 1 min 5 Final amplification 72 10 min 6 Cooling 16 ∞ Number of cycles (repetition of step 2-4) 30

Agarose gel electrophoresis

Agarose gel electrophoresis was done on a gel with concentration of 1,5%. 1,2 g of agarose was dissolved in 80 ml of 1x TBE buffer and the suspension was boiled in a microwave. After cooling the gel to approximately 50-60 °C, 80 µl of MIDORI dye binding DNA was added and then the gel was poured on an electrophoresis tray with a comb. After solidification (15 min) the tray with the gel was moved to the electrophoretic bath, comb removed and then covered with 1x TBE buffer, so the wells were below the liquid level. 10 µl of every sample was transferred to the separate wells along with 2 µl of 100 bp DNA ladder. Electrophoretic bath was plugged in power source with voltage of 130 V and the PCR products were separating for 30 mins. The gel was photo documented after the separation using imaging device.

Conjugation experiment

Selection of suitable antibiotic resistant recipient cells

Bacterial cultures were selected for appropriate resistance to antibiotics and were subsequently used in the course of conjugation experiment as recipient strains. First, the culture was incubated in sterile plastic tubes with 2 ml of LB containing serial dilution of adequate antibiotic. Recipient strains were then incubated in the shaking bath at 37 °C, 170 rpm overnight. The culture growing in the tube with the highest levels of concentration of the antibiotic was then reinoculated into a new serial dilution starting at higher level of concentration of the same antibiotic and was incubated again. The process was repeated until the point of the antibiotic resistance required for further use of selection of resistant bacterial strains. As an illustrative example, there may be a culture growing in the concentration of antibiotic of 25 mg/l after the first overnight incubation, while the aim is the MIC of 50 mg/l.

The culture is then reinoculated into the fresh sterile plastic tubes with 2 ml of LB with serial dilution of antibiotic starting at the point of 25 mg/l up to the concentration of 50 mg/l and is incubated again. Repeating these selection steps may lead to mutations that push the limit of antibiotic resistance in cells.

The selection was performed for the following bacterial strains:

• E. coli A15 AzidR for additional rifampicin resistance with MIC of 50 mg/l (RifR) → A15 RifR • E. coli UPEC536 RifR for additional sodium azide resistance with MIC of 100 mg/l (AzidR) → UPEC536 AzidR • E. coli ST131 RifR for additional sodium azide resistance with MIC of 100 mg/l (AzidR) → ST131 AzidR • E. coli UPEC536 RifR for additional kanamycin resistance with MIC of 25 mg/l (KanR) → UPEC536 KanR • E. coli ST131 RifR for additional kanamycin resistance with MIC of 25 mg/l (KanR) → ST131 KanR

Conjugation

Conjugation experiment requires the preparation of a donor strain carrying an antibiotic resistance plasmid and a recipient which will acquire the plasmid during the conjugative transfer. First, small amount of frozen stock of both donor and recipient was inoculated into the 50 ml of LB broth in the 250ml Erlenmeyer flask separately. There was also an addition of small amount of corresponding antibiotic according to the information about strains shown in previous chapters to exclude the possibility of contamination. The mixtures were cultivated overnight at 37 °C, 170 rpm. The overnight culture of the donor was then diluted 1:400 that is 125 µl of preculture in 50 ml of LB broth.

The optical density of donor bacterial cells (OD600) was measured regularly since this point using spectrophotometer and then the culture was placed back into an incubator at 37 °C, with constant shaking (170 rpm).

Conjugation was performed at these points of the growth phase of donor cells:

• Point A: Donor lag phase (OD600 = 0,05 - 0,07) • Point B: Donor middle exponential (exp) growth phase (OD600 = 0,7 - 0,8) • Point C: Donor stationary (stat) phase (OD600 > 1,5) 41

At each point (A, B, C), 500 µl of donor was pipetted into 1,5ml Eppendorf tube and centrifuged at 5000 rpm for 2 mins. Supernatant was discarded and then 50 µl of LB broth was added to resuspend the pellet. This mixture, that subsequently served as a donor control, was pipetted as a single drop to a sterile filter on LB agar plate. The donor control was used for counting the donor viable cells on plates without the addition of recipient cells. This served as a control of donor growth.

Similarly, 500 µl of recipient cells at the stationary phase only was pipetted into 1,5ml Eppendorf tube and centrifuged at 5000 rpm for 2 mins. Supernatant was discarded and then 500 µl of LB broth was added to resuspend the pellet and wash away the antibiotic from the cells. The recipient mixture was centrifuged again. This procedure was repeated one more time in order to completely wash away the antibiotic. After supernatant was discarded, 50 µl of LB broth was added to resuspend the pellet. Then, 500 µl of donor culture was added to the Eppendorf tube containing 50 µl recipient prepared in the previous steps. The bacteria mixture was homogenized by vortexing and centrifuged at 5000 rpm for 2 mins. Supernatant was discarded, and pellet was resuspended in 50 µl of LB broth. This mixture, that subsequently served as a conjugation mix, was pipetted as a single drop to a sterile filter onto LB agar plate.

The LB agar plates with filters were incubated at 37 °C for 1 hour. After incubation the filter from the plate was removed and placed into a tube containing 1 ml of physiological solution. Tubes were vortexed well to rinse the filters thoroughly and the mixture was then transferred into an Eppendorf tube. Serial dilution was made by mixing 100 µl of bacterial culture in physiological solution into a tube containing 900 µl of sterile physiological solution. Dilutions were made in technical triplicates up to 10-7.

Diluted mixtures were plated as follows:

• 6x20 µl drops of each dilution from conjugation mix was placed on selective LB agar plates with proper antibiotics to count the total number of transconjugants • 6x20 µl drops of each dilution from conjugation mix was placed on selective LB agar plates with proper antibiotics to count the total number of recipients • 6x20 µl drops of each dilution from donor control was placed on selective LB agar plates with proper antibiotics to count the total number of donors

Plates were then incubated at 37 °C overnight. The single colonies in drops were counted and then the frequency of transfer was calculated as the ratio of the number of transconjugants to the number of recipients, followed by t-test statistical analysis (p<0,05). 42

Fitness cost experiment

Knowledge of fitness cost mechanisms could help to dictate or at least to predict the development of antibiotic resistance in bacterial cells. The plasmid burden, which is usually manifested by decreased host fitness, may be determined by comparison of cell growth of plasmid-carrying bacteria with a plasmid-free cells as a negative control. Two distinct methods (manual and automated) of measurement of optical density (OD) were used for the determination of fitness cost of all ten plasmids within E. coli TOP10 cell only. The results from these methods were analogous so it was unnecessary to perform both methods for further experiments. Less time consuming, automated spectrophotometer method was then used for subsequent experiments of fitness cost of representative plasmids for bacteria of several species. Both methods were followed by statistical data analysis using the common Student’s t-test (p<0,05).

Manual spectrophotometer method

40 ml of LB broth in 250ml Erlenmeyer flask was inoculated in biological triplicates with 80 µl of overnight culture of bacterial strain containing the antibiotic resistance plasmid. The same was done with the negative control which was plasmid-free wild type bacterial strain. Optical density (OD600) of every sample was measured on spectrophotometer after the inoculation as the starting point (time 0). One of cuvettes was filled with 500 µl of LB broth as a blank, the rest was filled with 500 µl of the sample, measured and the values were written down. Then the flasks were placed into the shaking incubator at 37 °C, 170 rpm for 1 hour. OD600 measurement was taken at exact times - every hour in the lag phase (which corresponds to OD600 around 0,1) and every 30 mins in the exponential phase (which in the middle corresponds to OD600 around 0,9) until the start of stationary phase. Dilution 1:10 with LB was used due to spectrophotometer sensitivity after the point when the value of OD600 was above 0,9. All OD600 values obtained during the experiment were noted and evaluated. The negative control was used in order to compare the plasmid impact on the cell growth.

Automated spectrophotometer method using Tecan

The bacterial strains with plasmids were tested in biological triplicates in different media including LB, LB diluted 1:10, BHI, BHI diluted 1:10 and Minimal Medium with addition of glucose. Every well of a microtiter plate contained 1 ml of the medium and was inoculated with 5 µl of overnight bacterial culture carrying the antibiotic resistance plasmid. 43

Plasmid-free cells were also inoculated into the used media as a negative control. Sterile media with no bacterial strain was used as a control that no contamination has occurred. Optical density (OD600) of the cultures was measured every 30 mins using Tecan reader until the stationary phase was reached.

Persistence experiment

This experiment was conducted in order to demonstrate whether cells are losing plasmids at a time when plasmids are not necessary, i.e. at a time of no antibiotic selection pressure. The experiment was based on the procedure described by Cottell et al. (2014) where the plasmid persistence was determined by viable cell counts on selective media at 2 h, 12 h, 24 h and 48 h time points.

50 µl of overnight culture was inoculated into prewarmed (37 °C) LB broth without any antibiotic. At 12 h and 24 h time points 50 µl of culture was used to inoculate the 50 ml of fresh prewarmed (37 °C) LB broth without any antibiotic.

At 2 h, 12h, 24h and 48h time points the culture was diluted and plated on LB agar plates without any antibiotic in order to acquire 20-200 single colonies per plate after incubating the plates at 37 °C overnight. The 300 colonies for each time point and sample were transferred with a pick one by one to a selective LB agar plate and LB agar plate without antibiotic as a control. The plates were then incubated at 37 °C overnight. Evaluation was performed by comparison of paired plates, where cells that did not carry resistance plasmid were not growing on selective plates.

5. Results

The following section concisely summarizes the obtained results, which are then discussed in the section 6 Discussion.

Plasmid detection after transformation

Plasmid transformation via heat shock into competent cells was performed with the purpose of subsequent laboratory experiments aiming to study various plasmid characteristics such as horizontal transfer capabilities, burden for the host bacteria and the persistence in different hosts and environment without antibiotics.

Upon transformation the successful transfer of the antibiotic resistance plasmid into the recipient E. coli TOP10 cell was tested using the set of PCRs described in chapter 4.2.1. For this purpose, genes targeting IncX1, IncX2 and IncX3 plasmids as well as quinolone resistance genes qnrS1 and qnrB19 were tested. The gene amplification was visualized using gel electrophoresis (Figure 8). PCRs showed that all plasmids were successfully transferred via transformation into recipient cells and that all of them carried the expected antibiotic resistance gene. The transformants were later used in subsequent experiments to first select representative plasmids for each IncX group, then to assess the plasmids conjugation efficiency and finally to determine the plasmid fitness cost for the host and plasmid stability in the host cell.

Figure 8. Electrophoresis gel of successfully transformed plasmids in the E. coli TOP10 cells - top line showing assignment of plasmids to incompatibility groups X1 (red), X2 (green) or X3 (black); bottom line showing the presence of resistance genes qnrS (yellow) or qnrB (blue). 45

Selection of representative plasmids for each IncX group

In order to generalize the use of the results, representative plasmids were selected for each particular IncX group. Plasmids were selected via comparison of their burden on cell growth via manual spectrophotometer method, followed by verification via automated spectrophotometer method. The selected plasmids were intended for further use in later experiments.

Fitness cost of IncX plasmids via manual spectrophotometer method

First, the plasmids’ fitness costs were determined by following the growth of the host cells over time and comparing them with the plasmid-free host cells (E. coli TOP10, the blue line) as a negative control as seen in Figure 9. 4.500

4.000 TOP10 3.500 CE780h4 CE1551 3.000 615cip 2.500 HP103 HE40 OD600 2.000 CE1594 1.500 1456h8

1.000 HD76 HP2 0.500 194

0.000 0 10 20 30 40 50 time (h)

Figure 9. Growth of E. coli TOP10 carrying different IncX plasmids and the negative control (plasmid-free E. coli TOP10) using manual spectrophotometer method Not surprisingly little differences were spotted between the negative control and hosts carrying the new plasmids. To assess if any significant difference in growth rate was observed, the data from each host growth curve were statistically analysed using a Student's t-test (p<0,05) versus the plasmid-free control E. coli TOP10. The results are summarized in Table 8.

Table 8. Statistical analysis of growth rates of cells carrying plasmids compared to plasmid-free negative control E. coli TOP10.

The green values (p<0,05) represent significant differences in growth between cell carrying certain plasmid and the negative control while the red values represent similarity in cell growth.

T-test CE780h4 CE1551 615cip HP103 HE40 CE1594 1456h8 HD76 HP2 194 time (h) P= 0,05 lag 0 0,18350342 0,42264973 0,42264973 0,42264973 0,42264973 0,28918842 0,08753609 0,24458089 0,35300336 0,00036962 1 0,58571603 0,31747637 0,03409079 0,0885521 0,08106342 0,32749039 0,2201934 0,87401184 0,52859548 0,02337552 2 0,01352719 0,02454764 0,08245779 0,02103777 0,03641079 0,5079101 0,72670749 0,07417287 0,02073561 0,08728697 3 0,02278769 0,01653637 0,0128507 0,01193402 0,01616067 0,94541506 0,91091919 0,0556902 0,00281601 0,0274122 exp 3,5 0,00704641 0,0058432 0,01267696 0,00461109 0,01007979 0,06491836 0,19878726 0,02044503 0,00210586 0,02749663 4 0,03135489 0,00674089 0,0662514 0,00359794 0,02129026 0,05015485 0,13009422 0,03109848 0,0035073 0,01219435 4,5 0,02800508 0,00179138 0,01599159 0,00042823 0,00567267 0,02063258 0,13335027 0,00398675 0,0001277 0,00042705 5 0,4127858 0,0173965 0,06265172 0,01565596 0,02641378 0,53699156 0,90060447 0,06949488 0,00461077 0,01809757 5,5 0,89637303 0,00474323 0,1527387 0,01425527 0,04069796 0,3600973 0,61670535 0,01962957 0,00861507 0,05087412 6 0,63222291 0,12007888 0,23780713 0,00606264 0,01096391 0,80905272 0,87265709 0,04687861 0,01921195 0,03423272 6,5 0,37263192 0,41341154 0,44333006 0,00398493 0,01619445 0,56090769 0,98886619 0,02222428 0,04657308 0,00427246 7 0,67326291 0,23341257 0,66813618 0,05131445 0,02808177 0,39032727 0,04254915 0,50991195 0,09946101 0,04823761 7,5 0,5524397 0,52724809 0,59715565 0,19478525 0,10421897 0,21324136 0,50666528 0,30159917 0,67075262 0,30829977 stat 8 0,47718537 0,30839417 0,37996108 0,18019814 0,18288556 0,5127343 0,59439393 0,92637898 0,76798658 0,70895 9 0,27967815 0,62931359 0,5529976 0,28304827 0,37490582 0,37948829 0,3701811 0,05827992 0,8710013 0,47818342 24 0,20793551 0,73687417 0,91331228 0,37299087 0,60700711 0,24535227 0,15750138 0,07450263 0,07853368 0,09964699 48 0,71890865 0,22525662 0,3707374 0,17697562 0,07730653 0,01424388 0,03827303 0,03837373 0,25492565 0,48821317

T-test All 0,51805241 0,64120228 0,2032963 2,2595E-05 3,5658E-05 0,00358976 0,00693404 0,08305691 0,01961632 0,20049587

From Table 8 we can see that most of the growth variability between the plasmid- carrying and plasmid-free cells happens within the late lag phase and the early/mid exponential phase, while during the stationary phase the extent of variations are mainly not significant. Significant differences in growth were linked with a reduced growth rate with one exception, i.e. pCE780h4 which, interestingly, shows better growth values compared to the wild type strain until middle exponential phase.

Looking more in detail at each single plasmid data shows that IncX1 plasmids, namely pCE1551 and pHP2, seem to have a lower negative impact on the cell compared to other IncX groups. The only plasmids significantly not interfering with cell growth are pCE1594 from IncX2 and p1456h8 from IncX3. The most significant negative impact on the cells is caused by pHD76, belonging to the IncX3 group. Based on these results one representative plasmid for each group was pre-selected, namely: pHP2 for IncX1, p194 for IncX2 and p1456h8 and pHD76 for IncX3.

Fitness cost of IncX plasmids via automated spectrophotometer method

Automated spectrophotometer method was then used as a verification of the results obtained from the manual spectrophotometer method. As the name suggests this method is partially automated and potentially more accurate for OD measuring. Again, plasmid fitness costs for the host cell were determined by compiling the growth curves of plasmid carrying cells followed by a comparison with plasmid-free cells as the negative control as seen in Figure 10.

0.800

0.700 TOP10

0.600 CE780h4 CE1551 0.500 615cip HP103 0.400

OD600 HE40 0.300 CE1594 1456h8 0.200 HD76 HP2 0.100 194 0.000 0 10 20 30 40 50 time (h)

Figure 10. Growth of E. coli TOP10 carrying different IncX plasmids and the negative control (plasmid-free E. coli TOP10) using automated spectrophotometer method The data were statistically analysed (data not shown) and confirmed trends from the manual spectrophotometer method. Most of the plasmids showed negative impact for the host cell, IncX1 plasmids show the lowest negative impact for the host and while the IncX3 once more seems to cause the highest impact for the host cells. This is in agreement from previous finding (Figure 9 and Table 8). Similarly, according to the two methods, both the pre-selected plasmids pHP2 from IncX1 and p194 from IncX2 show a negative impact for host cells growth. Growth curves of representative plasmids compared to the plasmid-free control are highlighted in Figure 11 and Figure 12.

Based on the results of the fitness experiment as well as the current epidemiology and a recent study by Dobiasova and Dolejska (2016) that showed the existence of IncX1 and IncX2 epidemic lineages associated with PMQR genes, two plasmids were chosen for further experiments. In particular, plasmid pHP2 was selected as a representative of IncX1 group and plasmid p194 from IncX2 group. Experiments aiming to study plasmid lifestyle were performed during the course of this thesis.

4.500

4.000 TOP10 3.500 CE780h4 CE1551 3.000 615cip 2.500 HP103

OD600 2.000 HE40 CE1594 1.500 1456h8

1.000 HD76 HP2 0.500 194 0.000 0 10 20 30 40 50 time (h)

Figure 12. Growth of E. coli TOP10 with representative plasmids for IncX1 and IncX2 group (highlighted) compared to the negative control (E. coli TOP10 without plasmid) - manual spectrophotometer method

0.800

0.700 TOP10 0.600 CE780h4 CE1551 0.500 615cip HP103 0.400

OD600 HE40 0.300 CE1594 1456h8 0.200 HD76

0.100 HP2 194 0.000 0 10 20 30 40 50 time (h)

Figure 11. Growth of E. coli TOP10 with representative plasmids for IncX1 and IncX2 group (highlighted) compared to the negative control (E. coli TOP10 without plasmid) - automated spectrophotometer method

Conjugation experiment

Plasmids self-transfer was tested via conjugation by mixing donors (e.g. E. coli TOP10 carrying either pHP2 or p194) and recipient (e.g. E. coli A15) on membrane filters as described in Material and Methods. A series of conjugations were carried out as illustrated in Figure 13.

First, E. coli TOP10 carrying pHP2 or p194 obtained via transformation were used as plasmid donors for 5 different recipient strains Figure 13A. Then, upon confirmation of successful plasmids uptake, 4 out of 5 recipients were used as donors for a second round of conjugation Figure 13B.

In all cases transconjugants were selected on LB medium plates with 100 mg/l of ampicillin to select pHP2-carrying cells or 0,05 mg/l of tetracycline to select p194-carrying cells and the second antibiotic that served as the resistance marker of the recipient cells (100 mg/l of sodium azide, 50 mg/l of rifampicin, 50 mg/l of kanamycin or 25 of mg/l streptomycin). The second antibiotic was picked as explained in section 3.1 and 4.3.1 depending on the recipient strain. Transconjugants were later tested for ciprofloxacin susceptibility to demonstrate that they retain resistance to quinolone antibiotics. Successful horizontal gene transfer was demonstrated by PCR (data not shown) as explained in section 5.1.

Transfer frequencies were expressed as number of transconjugant colonies per number of recipient and compared to each other. Transconjugants were later used for experiments of fitness cost and plasmid stability.

Figure 13. Process diagram of individual conjugations (an arrow represents a single conjugation)

Frequency of plasmid transfer

Frequency of transfer for each plasmid in all the conditions tested was calculated as explained in Material and Methods. The results are listed and sorted by donor and recipient cells used in conjugation, representative plasmids and phase of growth in Table 9 and Table 10.

Table 9. Frequency of pHP2 transfer in conjugation during each phase of cell growth pHP2 Donor Recipient lag exp stat E. coli TOP10 E. coli A15 AzidR 1,41E-03 1,76E-02 6,98E-02 E. coli A15 AzidR E. coli A15 RifR 5,07E-06 1,01E-06 2,29E-05 E. coli TOP10 P. aeruginosa 481/02 9,36E-08 1,54E-07 3,95E-07 E. coli TOP10 S. enteritidis FA-8065 4,65E-07 2,58E-05 5,14E-05 S. enteritidis FA-8065 E. coli UPEC536 KanR 9,95E-09 1,66E-07 2,07E-06 S. enteritidis FA-8065 E. coli ST131 KanR 3,32E-08 1,06E-08 6,13E-07 E. coli TOP10 E. coli UPEC536 RifR 5,56E-09 2,77E-06 3,74E-07 E. coli TOP10 E. coli ST131 RifR 6,48E-09 2,32E-08 1,85E-08 E. coli UPEC536 RifR E. coli UPEC536 AzidR 9,89E-02 3,89E-01 4,53E-01 E. coli ST131 RifR E. coli ST131 AzidR 2,06E-04 1,01E-04 8,85E-04

Table 10. Frequency of p194 transfer in conjugation during each phase of cell growth p194 Donor Recipient lag exp stat E. coli TOP10 E. coli A15 AzidR 7,11E-06 5,34E-05 1,53E-05 E. coli A15 AzidR E. coli A15 RifR 7,66E-07 5,89E-07 1,67E-06 E. coli TOP10 P. aeruginosa 481/02 ND ND ND E. coli TOP10 S. enteritidis FA-8065 6,60E-08 1,90E-06 2,85E-06 S. enteritidis FA-8065 E. coli UPEC536 KanR 1,60E-08 2,38E-08 1,69E-08 S. enteritidis FA-8065 E. coli ST131 KanR 4,19E-08 6,98E-09 2,98E-07 E. coli TOP10 E. coli UPEC536 RifR ND ND 1,40E-08 E. coli TOP10 E. coli ST131 RifR ND 3,30E-09 7,79E-09 E. coli UPEC536 RifR E. coli UPEC536 AzidR ND ND ND E. coli ST131 RifR E. coli ST131 AzidR ND ND ND ND = no plasmid transfer was detected

Interestingly, various effects were observed when testing the mobility of p194 and pHP2.

During the first round of conjugations from E. coli TOP10 as the donor to E. coli A15 AzidR as the recipient, the frequency of pHP2 transfer increased from 1,41x10-3

52 transconjugants per recipient in lag phase to up to one order of magnitude in exponential phase (1,76x10-2) and by another half order of magnitude in stationary phase (6,98x10-2). This trend seems to be consistent in all the transfer experiments regarding pHP2 and p194 (Table 9 and Table 10).

Notably, substantial differences in frequency of transfer arose between IncX groups. In almost all the conditions tested IncX1 plasmid, pHP2, showed compelling higher transfer rate than p194 from IncX2. For example, the frequency of pHP2 transfer from E. coli TOP10 as the donor to strain E. coli A15 exceeded the p194 transfer by 3 orders of magnitude. Moreover, in three cases, from E. coli TOP10 to P. aeruginosa 481/0, from E. coli UPEC536 RifR to E. coli UPEC536 AzidR and from E. coli STR131 RifR to E. coli ST131 AzidR, the p194 transfer was not detectable, while pHP2 transfer was.

Of interest, when looking at the transfer rate between pathogenic strains it is possible to notice that transfer of pHP2 from E. coli UPEC536 RifR to E. coli UPEC536 AzidR showed surprisingly high frequency of transfer (9,89x10-2 in lag phase up to 4,53x10-2 in stationary phase) compared to other conjugations.

Meanwhile comparing the transfer to lab strains versus pathogenic strains we can see that frequency of transfer between cells with the similar pathogenicity showed very high values of efficiency. Finally, the transfer from laboratory strain to another laboratory strain showed higher frequency than from laboratory strain to pathogenic strain. These results seem to suggest that similar genetic context can facilitate the mobility of plasmids.

All the data concerning the frequency of plasmid transfer were subjected to statistical analysis via the t-test so to assess the significant differences, if any, of transfer frequencies among all growth’s phases. These results are listed in Table 11 and Table 12.

From these tables we can clearly see pHP2 transfer in lag phase is significantly lower than in exponential and stationary phases, and this is true for almost all the conjugation experiments. Also, in lot of the cases the exponential and stationary phase transfer rates are not significantly different. These findings suggest that at least for pHP2 the transfer reach its peak of efficiency during exponential growth.

A similar trend can also be observed for p194, though in this case the differences are less appreciable. We have to acknowledge that the generally lower number of transconjugants detected for p194 can have been a source of uncertainty when performing the statistical test, because they were more subject higher variability during biological repetitions. 53

Table 11. Statistical analysis of pHP2 transfer rate. The green values (p<0,05) represent significant difference between the phases of growth while the red values represent similarity in cell growth. pHP2 T-test P= 0,05 lag exp stat E. coli TOP10 to E. coli A15 AzidR lag 0,0412553 0,0286688 exp 0,0751073 lag exp stat E. coli A15 to E. coli A15 RifR lag 0,013098 0,034123 exp 0,023115 lag exp stat E. coli TOP10 to P. aeruginosa 481/02 lag 0,135923 0,003564 exp 0,009005 lag exp stat E. coli TOP10 to S. enteritidis FA-8065 lag 0,03326 0,027492 exp 0,193561 lag exp stat S. enteritidis FA-8065 to E. coli UPEC536 lag 0,012095 0,203434 KanR exp 0,230653 lag exp stat S. enteritidis FA-8065 to E. coli ST131 lag 0,43938 0,09641 KanR exp 0,085601 lag exp stat E. coli TOP10 to E. coli UPEC536 RifR lag 0,016092 0,00271 exp 0,020213 lag exp stat E. coli TOP10 to E. coli ST131 RifR lag 0,120579 0,1381127 exp 0,5328881 lag exp stat E. coli UPEC RifR to E. coli UPEC AzidR lag 0,099248 0,020805 exp 0,475517 lag exp stat E. coli ST131 RifR to E. coli ST131 AzidR lag 0,159532 0,064885 exp 0,070586

Table 12. Statistical analysis of p194 transfer rate. The green values (p<0,05) represent significant difference between the phases of growth while the red values represent similarity in cell growth. p194 T-test P= 0,05

0 lag exp stat E. coli TOP10 to E. coli A15 AzidR lag 0,049314 0,049966 exp 0,080461 lag exp stat E. coli A15 to E. coli A15 RifR lag 0,4596041 0,0882536 exp 0,0141201

E. coli TOP10 to P. aeruginosa 481/02

lag exp stat E. coli TOP10 to S. enteritidis FA-8065 lag 0,005909 0,061845 exp 0,255351 lag exp stat S. enteritidis FA-8065 to E. coli UPEC536 lag 0,303793 0,9101817 KanR exp 0,5847772 lag exp stat S. enteritidis FA-8065 to E. coli ST131 lag 0,387079 0,1901173 KanR exp 0,1130921

E. coli TOP10 to E. coli UPEC536 RifR

lag exp stat E. coli TOP10 to E. coli ST131 RifR lag 0,189508 0,1077256 exp 0,3381584

E. coli UPEC RifR to E. coli UPEC AzidR

E. coli ST131 RifR to E. coli ST131 AzidR

☒ = no statistical analysis was performed since no plasmid transfer was observed

Fitness cost of IncX plasmids related to host background and cultivation media

Automated spectrophotometer method measuring optical density (OD) during cell growth was used to assess fitness cost of both representative plasmids, pHP2 and p194, in all host cells obtained during the above described conjugation experiments and in 5 different cultivation media, LB, LB diluted 1:10, BHI, BHI diluted 1:10 and MM with addition of glucose.

The individual tendencies of growth in various media did not fundamentally differ from each other (data not shown). In order to unify and assess trends of plasmid fitness cost, the result values from individual tests were transferred into deviations of OD representing growth of plasmid-carrying cell from the OD representing growth of plasmid-free cell in each media. These deviations were averaged for distinct growth phases for each cell strain. These fitness costs are demonstrated as charts in Figure 14.

All the data concerning fitness cost via automated spectrophotometer method were subjected to statistical analysis. Due to the fact that the t-test was not available for use in this method, the deviations were transferred to percentage representing differences in growth of plasmid-carrying cells from plasmid-free negative control. The limit difference determining significance was set at 5%. These results are listed in Table 13.

From Table 13 we can see that plasmid burden on host cell is linked to a reduced cell growth with some exceptions, i.e. exponential growth phase of P. aeruginosa carrying the plasmid pHP2, where the cell growth was increased nearly by 14,8%. The second exception forms an exponential growth phase of E. coli ST131 AzidR carrying the plasmid pHP2, where the cell growth was increased nearly by 26,88%. Significant differences in growth of pHP2- carrying cells are predominantly in lag phase and then gradually decline. While significant differences in growth of p194-carrying cells are in lag and exponential phase and decline at stationary phase.

In comparison of both plasmids, the IncX2 representative, p194, causes significantly higher fitness cost to the host cell. For example, in the exponential phase of E. coli UPEC536 AzidR the pHP2-carrying cell’s growth rate was lowered by 8,48%, while the p194-carrying cell’s growth rate was lowered nearly by 32,3%.

E. coli TOP10 E. coli A15 AzidR E. coli A15 RifR 0.6 0.8 0.8 0.6 0.6 0.4

0.4 0.4

OD600 OD600 OD600 0.2 0.2 0.2 0 0 0 lag exp stat lag exp stat lag exp stat

HP2 194 Control HP2 194 Control HP2 194 Control

P. aeruginosa S. enteritidis E. coli ST131 AzidR 0.8 0.8 0.8 0.6 0.6 0.6

0.4 0.4 0.4

OD600 OD600 OD600 0.2 0.2 0.2 0 0 0 lag exp stat lag exp stat lag exp stat

HP2 Control HP2 194 Control HP2 194 Control

E. coli ST131 RifR UPEC536 AzidR UPEC536 RifR 0.8 0.8 0.8 0.6 0.6 0.6

0.4 0.4 0.4

OD600 OD600 0.2 OD600 0.2 0.2 0 0 0 lag exp stat lag exp stat lag exp stat

HP2 194 Control HP2 194 Control HP2 194 Control

UPEC536 KanR E. coli ST131 KanR 0.8 0.8 0.6 0.6 Figure 14. Plasmid fitness 0.4 0.4

cost on host cells by phases

OF600 OD600 of growth 0.2 0.2 0 0 lag exp stat lag exp stat HP2 Control HP2 Control

Table 13. Statistical analysis of fitness cost of representative IncX plasmids for host cell. The green values represent significant difference in growth between plasmid-carrying cell and plasmid-free negative control. The red values represent similarities in cell growth. pHP2 p194 Deviation in percentage lag exp stat lag exp stat E. coli TOP10 -20,0647 -3,64944 -3,18627 -23,8282 -6,05024 -2,54559 E. coli A15 AzidR -9,00148 -1,40615 -0,9256 -17,9233 -2,93839 -0,24814 E. coli A15 RifR -17,5354 -0,30124 -5,84772 -21,6423 -17,5956 -2,79537 P. aeruginosa 481/02 4,295442 14,79698 -0,43846 - - - S. enteritidis FA-8065 -15,7203 -18,6116 -12,0124 -26,4175 -31,4668 -9,90177 E. coli ST131 AzidR -17,4188 26,87602 -1,65614 -28,945 -28,8731 -18,5291 E. coli ST131 RifR -17,1155 -3,65914 -6,66189 -30,4497 -40,6266 -27,5187 E. coli UPEC536 AzidR -20,5986 -8,48344 -8,32365 -31,7847 -32,2969 -10,3765 E. coli UPEC536 RifR -22,3196 -12,2469 -10,1402 -30,3451 -25,4667 -13,0595 E. coli UPEC536 KanR -25,7155 -6,16011 -5,70333 - - - E. coli ST131 KanR -22,5185 -4,82858 -2,69646 - - - The minus values represent the decreased growth of bacterial culture while positive ones represent the increased growth of bacterial culture.

Persistence experiment

The persistence experiment was used to determine the success of plasmid stability. All pHP2- and p194-carrying cells of different host background from previous experiments were tested whether they lose their plasmids under certain conditions. Host cells were cultured in LB broth and then tested for plasmid persistence as showed in Methods.

None of the plasmids, pHP2 or p194, showed the difference in the persistence in various strains since they were retained during the whole course of the experiment even after 48h (Table 14).

Table 14. Plasmid stability within different host bacteria cultured in LB broth without antibiotics

Plasmid stability pHP2 p194 Host cell 2h 12h 24h 48h 2h 12h 24h 48h E. coli TOP10 100% 100% 100% 100% 100% 100% 100% 100% E. coli A15 AzidR 100% 100% 100% 100% 100% 100% 100% 100% E. coli A15 RifR 100% 100% 100% 100% 100% 100% 100% 100% P. aeruginosa 481/02 100% 100% 100% 100% - - - - S. enteritidis FA-8065 100% 100% 100% 100% 100% 100% 100% 100% E. coli ST131 AzidR 100% 100% 100% 100% 100% 100% 100% 100% E. coli ST131 RifR 100% 100% 100% 100% 100% 100% 100% 100% E. coli UPEC536 AzidR 100% 100% 100% 100% 100% 100% 100% 100% E. coli UPEC536 RifR 100% 100% 100% 100% 100% 100% 100% 100% E. coli UPEC536 KanR 100% 100% 100% 100% - - - - E. coli ST131 KanR 100% 100% 100% 100% - - - - Since there was no p194 transfer in 3 bacterial strain (labelled “-“), the persistence experiment was not performed

PCRs targeting qnrS1 gene of one random colony for every time point, strain and plasmid was performed to confirm the plasmid is within the host cell (the result not shown).

6. Discussion

An important role in the increasing prevalence of bacteria resistant to antimicrobial agents is the effective horizontal transfer of mobile genetic elements (MGEs), in particular of plasmids carrying the antibiotic resistance genes. One of the most important mechanisms of antibiotic resistance is plasmid-mediated quinolone resistance (PMQR) targeting quinolone antibiotics, that are widely used in human and veterinary medicine.

With regard to the use of the antimicrobials for food-producing animals, the antibiotic consumption is rising globally with the increasing human demand for animal protein. Boeckel (2015) in his research stated that the annual antibiotic consumption in 2010 was 45 mg (for cattle), 148 mg (for chicken) and 172 mg (for pigs) of antibiotics per one kilogram of animal protein. That means approximately 63,151 tons of antimicrobials consumed in 2010 globally for animals only that is about a half of annual antibiotic production. The study also predicted an estimated increase, driven by growth in consumer demand for animal products in lower- income countries, of global antibiotic consumption by 67% till year 2030 (Boeckel et al. 2015).

Meanwhile the antibiotic resistant bacteria are not lagging behind in dissemination of fluoroquinolone resistance to other hosts. The spread of resistant bacteria subsequently influences veterinary and human medicine. In bacteria of Enterobacteriaceae (E. coli, Klebsiella spp.) isolated in United Kingdom the fluoroquinolone resistance rose from 6 % to 20% in just 5 years, from 2001 to 2006. During the following years the percentage of resistant isolates was slightly lowered as a result of prescription of different antibiotics for patient treatment (Livermore et al. 2013; Redgrave et al. 2014). Similarly, from 2002 to 2009 infections caused by fluoroquinolone resistant or multiresistant E. coli showed a serious increase up to 39 % in Europe (Gagliotti et al. 2011).

The above mentioned are just two examples highlighting the emergency situation that the society is facing. There is indeed a high possibility that antibiotic resistant bacteria will outrun the development of new antibiotic agents and if not solved differently, morbidity and mortality will escalate to the point of “renewed” pre-antibiotic era. These apprehensions drive society and predominantly researchers to comprehend mechanisms and interactions of antibiotic resistant cells to develop a way out of crisis (Barriere 2015).

Since the dissemination of plasmids is among the most important drivers of increasing resistant to antibiotics in bacteria relevant for the health of humans and animals, the aim of this thesis was to determine the fitness burden caused by resistance plasmids and their stability within the host cell. This goal was achieved by methods shown in previous chapters.

Frequency of conjugative transfer of IncX plasmids into various recipient cells including laboratory and wild-type pathogenic strains of several species

Conjugation of representative IncX plasmids, pHP2 for IncX1 and p194 for IncX2, into all the recipients was successful with the exception of p194 transfer from E. coli TOP10 to P. aeruginosa 481/0, from E. coli UPEC536 RifR to E. coli UPEC536 AzidR and from E. coli STR131 RifR to E. coli ST131 AzidR. These exceptions occurred probably due to low rate of IncX2 plasmid conjugative transfer. Another reason for unsuccessful transfer of p194 into P. aeruginosa may be that some PMQR-carrying plasmids cannot successfully replicate within this host (Jiang et al. 2014).

Overall the IncX1 plasmids showed higher frequency of transfer than IncX2 plasmids. Interesting results were obtained for the conjugation of plasmid pHP2 from E. coli UPEC536 RifR to E. coli UPEC536 AzidR where transfer rate was extremely high. This comparison of transfer rates of IncX subgroups is first of its kind and has not been taken into account before. These plasmid families likely play a crucial part of the process of dissemination of resistance to quinolone antibiotics. However, Gama et al. (2017) noted that it is very unlikely to associate the frequency of transfer with the incompatibility groups.

Another intriguing result was detected in conjugative transfer with focus on the strain pathogenicity. There was a significant difference between the plasmid transfer to laboratory and pathogenic strains. Generally, the transfer from laboratory strain to another laboratory strain showed higher frequency than from laboratory strain to pathogenic strain. Moreover, once plasmid is transferred from pathogenic to another pathogenic strain, the frequency of plasmid transfer increase. These results support the idea that similar genetic background can promote the mobility of plasmids, which has not been observed in any publication so far.

Differences in transfer rates between IncX groups may have various origins. The cause of diverse frequency of conjugative transfer is still not fully elucidated, but we can speculate that one possibility could be an upregulation of plasmid transfer proteins. Indeed as Møller et al. (2017) showed, in IncI1 the antibiotic-mediated upregulation of transfer proteins encoded 61 by genes for the pilus synthesis, the assembly system (traF and traL), the DNA transfer system (traI and traM) and structural components of the pilus (pilS), resulting in significant increase of conjugation transfer. Another mechanism responsible for different conjugative transfer may be the quorum sensing or sensing of environmental conditions with regulatory systems activating the tra genes (Koraimann and Wagner 2014). This is supported by study published by Händel et al. (2015) that showed the transfer rate of E. coli carrying IncI1 plasmids containing genes for extended-spectrum β-lactamase (ESBL) and noted that plasmid transfer highly correlates with the availability of nutrients as a source of energy.

Meanwhile, Lopatkin et al. (2017) offered a different view on shifting of plasmid transfer. In this study they applied a selection pressure or stress such as non-inhibitory levels of antibiotics or temperature change to cells during conjugation. It consequently may play a role in conjugative transfer. However, the study also stated that the antibiotics can provide a selection advantages for transconjugants but also can inhibit parents and reduce their population size. Nevertheless, to get better comprehension of IncX plasmid lifestyle, it would be intriguing to repeat the transfer experiments and test the impact of different stress conditions such as the presence of antibiotic and the temperature shift.

Burden of IncX plasmids for host bacteria of several species carrying these plasmids

IncX1 and IncX2 plasmid fitness cost was successfully determined using automated spectrophotometer method in different media and then averaged into unified hypothesis. Results proved that IncX plasmids cause burden for host cells with two following exceptions. The growth of P. aeruginosa carrying plasmid pHP2 increased nearly by 14,8% in exponential growth phase compared to the plasmid-free negative control. Similarly, the fitness of E. coli ST131 AzidR carrying plasmid pHP2 increased nearly by 26,88% in exponential growth phase. Possible explanation behind these exceptions may be the specific chromosomal mutations as noted in publication by Machuca et al. (2014) concerning qnrS1 gene that resulted in increased fitness of bacterial host.

Meanwhile, the pHP2 plasmid fitness cost for the host cell was significantly different predominantly in lag phase and declined in later phases, while p194 fitness cost has significantly reached up to the exponential phase and then declined. In some cases, especially with p194, the plasmid burden reached values up to 1/3 of plasmid-free cells. In order to determine the reason behind the fitness cost of plasmids carrying quinolone resistance,

Machuca et al. (2014) established a hypothesis, that PMQR genes carried by these plasmid stay behind the cause of burden for host cell. They were able to prove their hypothesis qnrA1 and qnrS1 genes carried by plasmids pose a cost for their bacterial hosts. In a following study, Machuca et al. (2016) stated that aac(6′)-Ib-cr gene, which expression is responsible for minor increase of quinolone resistance, also causes a significant increase of fitness cost and therefore confirms previous study where PMQR genes negatively affects the growth of host bacteria.

Therefore, the effect of the plasmid fitness cost could be withdrawn by the mutations in genes encoding for unneeded plasmid proteins. These proteins cause significant energetic burden for the host bacteria and mutations within the encoding genes may increase the fitness of the plasmid-carrying cell. Therefore, the transcriptional regulation is a way of notable importance to minimize plasmids cost (Shachrai et al. 2010; San Millan and MacLean 2017).

On the other hand, it has been shown that mutations within gyrA gene reduce fitness of E. coli strains by approximately 6% (Redgrave et al. 2014; Händel et al. 2015). However, these are genes encoded by bacterial chromosomes and the mechanisms compared to PMQR genes can be different. The relationships between resistance genes, mutations and bacterial fitness are complex. Unfortunately, there are not many studies focused on this problem available, therefore, further research in this area is needed.

Stability of representative IncX plasmids in host cells without antibiotic selective pressure

Experiments conducted with this thesis showed that IncX plasmids were able to persist within the host cell in the antibiotic-free environment for more than 48h regardless the fact that the host cell lacked the need for it to provide antibiotic resistance. These results were obtained by method based on Cottell et al. (2012, 2014). These publications are focused on assessing the plasmid stability by silencing the plasmid target regions. The effort to decrease the plasmid stability by disrupting the gene for resistance did not affect the plasmid persistence or even the fitness cost. These studies demonstrated that plasmids carrying antibiotic resistance gene for β-lactams persisted in host bacteria (Cottell et al. 2012).

The question remains: “What mechanism enables the plasmid to remain within the host cell?”. The first possibility is shown in the introduction of this thesis and is related to the toxin/antitoxin (TA) system carried by plasmids. In the case the plasmid, that carries TA system, is lost, the remaining toxin interferes with the cell and inhibits the cell growth. However, when the TA system is not present in plasmid, there are more possible answers of 63 their successful persistence in host bacteria. First one was proposed by Carroll and Wong (2018) and stated that high plasmid transfer rates may be the reason behind plasmid persistence. Horizontal plasmid transfer keeps the plasmid stability at balance. The other possibility is that the plasmid burden is decreased by mutations in plasmid genes which consequently minimizes the advantages of losing the plasmid and therefore the plasmid withdrawal does not occur (San Millan et al. 2014; Händel et al. 2015).

These possible mechanisms of acquiring the plasmid stability probably explain how the plasmid is kept within the host cell but they do not offer an exploitable way of the plasmid elimination from the cells. The dissemination of resistance plasmids widely occurs, and we do not know how to effectively prevent it from happening. One solution to at least postpone the problem is withdrawal of needless antibiotics misuse in food-producing animals. Some of the countries already prohibited antibiotic use in spite of short-term adverse economic aspect. Data suggests that restrictions on antibiotic use to support individual animal growth can be applied with negligible impact to production (Lhermie et al. 2017). The antimicrobial agents important for human medicine which were used also as growth promoters in agriculture were limited to human medicine only by agreement in 1999 in Switzerland (Boerlin et al. 2001). Thereafter in 2006 the prohibition of use of antibiotics to support animal growth came into force for all states of the European Union and Switzerland (European Commission - Press release 2005; Cogliani et al. 2011). Withdrawal of fluoroquinolone use in poultry in USA was introduced in 2005 (Collignon 2005). Since 2017, the antibiotics are banned for use to promote animal growth throughout the USA (VFD - Veterinary Feed Directive 2017). In late 2016, China prohibited colistin as an animal feed additive (Walsh and Wu 2016).

Nevertheless, this will not solve the problem of prevailing resistance plasmids entirely, therefore more experiments with different growing conditions and setting need to be done in the future to fully assess the plasmid persistence.

7. Conclusion

Mobile genetic elements (MGEs) carrying genes for antibiotic resistance impose a serious threat to human welfare. MGEs, and plasmids in particular, play a crucial role in the dissemination of genes encoding for the antibiotic resistance. In order to prevent possible crisis of ineffective antibiotics and wide spread of infections caused by resistant bacteria, knowledge of the plasmid lifestyle is necessary. Acquaintance of plasmid behaviour and characteristics, especially their weaknesses, may lead to a targeting their disadvantages in future drug development. This thesis was aimed at specific plasmid group associated with quinolone resistance genes, IncX family, their frequency of conjugative transfer, fitness cost and stability in host bacteria.

The results from conjugation experiment showed significant differences in frequency of transfer in plasmids from different subgroups. IncX1 plasmids represented by pHP2 reported higher transfer rate compared with IncX2 subgroup represented by p194. Moreover, the differences of plasmid transfer abilities between the growth phases of bacteria that served as donors of these plasmid noted the tendency of higher transfer rate in later phases. And finally, results indicated the similar bacterial genetic background may promote the mobility of plasmids.

The outcome from experiment on fitness cost was the expanded knowledge about plasmid burden. Plasmid fitness cost is predominantly associated with the decrease of cell growth with some exceptions. In comparison to IncX subgroups, plasmids from IncX2 family caused significantly higher burden for host bacteria. Additionally, plasmids repress the cell growth especially in earlier phases. These findings suggested that there must be some kind of adaptation to the plasmid interference.

And finally, the persistence experiment showed that plasmids were maintained in laboratory and pathogenic bacteria regardless the fact that resistance plasmids are usually not necessary when a cell is present in antibiotic-free environment. This data gives us an idea that plasmids have mechanisms to be stably maintained in the host bacteria.

Nonetheless, this thesis is only a small fraction of knowledge needed to fully comprehend the lifestyle of antibiotic resistance plasmids and therefore, more research in this field is suggested.

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9. Appendices

A B

C D

Figure 15. Demonstration of experiments. A, B - Plates for conjugation experiment; C - Microtiter plate for automated spectrophotometer method; D - Persistence experiment

Figure 16. pHP2 plasmid map

Figure 17. p194 plasmid map

10. List of abbreviations

BHI Brain heart infusion

DNA Deoxyribonucleic acid

F-factor Fertility factor

HGT Horizontal gene transfer

Inc Incompatibility

IS Insertion sequence

MDR Multidrug-resistance

MGE Mobile genetic element

MIC Minimal inhibitory concentration

MM Minimal Medium

Mpf Mating pair formation structure

LB Luria-Bertani/Lysogeny broth

PCR Polymerase chain reaction

OD Optical density

ORF Open Reading Frame oriT Origin of transfer oriV Origin of vegetative replication

PBRT PCR-based replicon typing

PMQR Plasmid-mediated quinolone resistance

QRDR Quinolone-resistance-determining region

Rep Replication initiator protein

RTF Resistance transfer factor

Ssb Single-strand binding protein ssDNA Single-strand DNA

ST Sequence type

STI Sexually transmitted infection

TA Toxin/antitoxin

Tn Transposon

UPEC Uropathogenic Escherichia coli

UTI Urinary tract infection