Determining the mechanisms of resistance to drug combinations and their fitness effects in Candida albicans

by

Jessica Anne Hill

A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy

Department of Molecular Genetics University of Toronto

© Copyright by Jessica A. Hill 2014

ii

Determining the mechanisms of resistance to drug combinations

and their fitness effects in Candida albicans

Jessica Anne Hill

Doctor of Philosophy

Department of Molecular Genetics University of Toronto

2014

Abstract

The evolution of drug resistance is occurring rapidly and threatening our arsenal of

antimicrobials. This is a poignant issue with antifungals, whose targets are limited due to

conservation between fungi and the human host. A promising strategy is to enhance

effectiveness of our current antifungals using combination therapy. Adding an inhibitor of one

of the key stress response proteins, Hsp90 or calcineurin, to an antifungal azole renders the

activity of the azole fungicidal and abrogates azole resistance. However, evidence from clinical

isolates indicates that resistance to the drug combination can still arise. Determining the

mechanisms of resistance to these drug combinations and their fitness effects will provide

information about how resistance can occur and whether it is likely to spread in a population. To

address what mechanisms of resistance can arise to drug combinations, I evolved strains of the

leading fungal pathogen, Candida albicans, and its genetically tractable relative Saccharomyces

cerevisiae, in the presence of an azole and the Hsp90 inhibitor geldanamycin (GdA) or the

calcineurin inhibitor FK506. The vast majority of strains (286) went extinct, however, I

identified and validated mechanisms of resistance in 13 strains. A variety of resistance

mechanisms were found, from well-established resistance mechanisms to novel ones. To

address the fitness effects of resistance to an azole in combination with GdA or FK506, I took

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advantage of these C. albicans in vitro evolved strains and a series of C. albicans clinical

isolates that transition to Hsp90- and calcineurin-independent azole resistance. I determined that

resistance to the drug combination is often but not universally costly in the absence of drug and

in novel, clinically relevant stress environments. Together these results provide a basis for our

understanding of key parameters for the evolution of resistance to drug combinations: the

variety of mechanisms that encompass resistance, and their fitness costs.

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Acknowledgments

The successful completion of this thesis would not have been possible without several

individuals.

I am indebted to my supervisor, Leah Cowen, under whose guidance I have grown to become a

better scientist. Leah’s commitment to effective communication, elegant design and

thoroughness will stay with me beyond this degree, as well as her commitment to supporting her

students.

I have had the pleasure of working with Aneil Agrawal, William Navarre and Corey Nislow. As

a supervisory committee, Aneil, Will and Corey have been consistently supportive and

insightful and I would like to recognize their influence on this body of work.

My time in the Cowen lab afforded me the opportunity to meet some incredible scientists and

people. Throughout the years my lab mates may have changed but they all share a passion for

science. I will miss the stimulating scientific conversations in the Cowen lab. All the more I will

miss the special friendships I have formed in this lab, because no one can understand the

challenges of grad school the way your lab mates can. I would like to especially thank Rebecca

Shapiro, Sheena Singh, Nicole Robbins, Michelle Leach, Teresa O’Meara, Tanvi Shekhar-

Guturja, Elizabeth Polvi, Amanda Veri and Cathy Collins.

Beyond the lab, there have been a number of scientists in my life whose friendship, support and

curiousity has not been diminished by time or physical separation. I cannot imagine how

finishing this degree would have looked without their involvement, nor would I want to. I am

especially grateful to Heather Maughan, Dilara Ally and Aleeza Gerstein for their friendship and

insights. My non-scientist friends have been instrumental in the completion of this degree. Over

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a period of time that has included many difficulties in my life, I have gratefully received

support from Chioma Ume, Andrea Benvenuto and Dave Seevaratnam, among others. I cannot

adequately thank these people.

I am eternally grateful for the love and support of my family. My sister, Kelly Hill, has been the

bedrock of my support and her persistence in life and commitment to high standards has been an

inspiration. I would also like to thank my brother-in-law, Gabe Plener, for his unwavering

support. My grandparents, Theresa and Michael Illes, and Margaret and George Hill, had been

incredibly influential and loving; they showed me that hard work is a requirement for success.

Finally, I must thank my parents, Anne and Lawrence Hill, for their unconditional love and

support, and for giving me the freedom to pursue my interests. I dedicate this work to their

memory.

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Table of Contents

Acknowledgments ........................................................................................................................ iv

Table of Contents .......................................................................................................................... vi

List of Tables ................................................................................................................................. x

List of Figures ............................................................................................................................... xi

List of Abbreviations .................................................................................................................. xiii

Chapter 1 Introduction ................................................................................................................... 1

1 Introduction ............................................................................................................................. 1

1.1   Evolution of drug resistance in microbes ......................................................................... 1  

1.2   Candida albicans .............................................................................................................. 3  

1.3   Antifungal drugs ............................................................................................................... 5  

1.3.1 Major antifungal drugs and their mode of action ....................................................... 5

1.3.2 Drug resistance mechanisms 8

1.4   Strategies for thwarting the evolution of drug resistance ............................................... 15  

1.4.1 Developing new antifungals ..................................................................................... 15

1.4.2 Combination therapy ................................................................................................ 15

1.4.3 Targeting stress response: Hsp90 and calcineurin ................................................... 16

1.5   Natural variation in resistance to antifungal drugs ......................................................... 20  

1.5.1 Variation between species ........................................................................................ 20

1.5.2 Variation between strains ......................................................................................... 23

1.5.3 Variation within a population .................................................................................. 24

1.6   Strategies for studying the evolution of drug resistance ................................................. 26  

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1.6.1 Examining clinical isolates ...................................................................................... 26

1.6.2 Using experimental evolution .................................................................................. 31

1.7   Thesis rationale ............................................................................................................... 36  

Chapter Two Genetic and Genomic Architecture of the Evolution of Resistance to Antifungal

Drug Combinations ...................................................................................................................... 39

2 Genetic and Genomic Architecture of the Evolution of Resistance to Antifungal Drug

Combinations ............................................................................................................................... 40

2.1   Introduction .................................................................................................................... 40  

2.2   Materials and Methods ................................................................................................... 44  

2.2.1 Strains and culture conditions .................................................................................. 44

2.2.2 Strain construction ................................................................................................... 50

2.2.3 Plasmids and oligonucleotides ................................................................................. 56

2.2.4 Plasmid construction ................................................................................................ 61

2.2.5 Evolution experiment ............................................................................................... 63

2.2.6 Minimum inhibitory concentration and checkerboard assays .................................. 69

2.2.7 Genome sequencing ................................................................................................. 70

2.3   Results ............................................................................................................................ 73  

2.3.1 Experimental evolution of C. albicans and S. cerevisiae yields resistance to the

combination of an azole and an inhibitor of Hsp90 or calcineurin ...................................... 73

2.3.2 Cross-resistance assays as a strategy to predict distinct mechanisms of resistance . 80

2.3.3 Mutations in HSP90 confer resistance to azole and geldanamycin in two S.

cerevisiae lineages and one C. albicans lineage .................................................................. 83

2.3.4 Mutations in FPR1 confer resistance to azole and FK506 in two S. cerevisiae

lineages ................................................................................................................................ 89

viii

2.3.5 Whole genome sequencing identifies candidate resistance mutation in additional

S. cerevisiae evolved lineages ............................................................................................. 93

2.3.6 Whole genome sequencing identifies extensive aneuploidy in four of the C.

albicans evolves lineages, and additional candidate resistance mutation in two of the C.

albicans lineages ................................................................................................................ 100

2.4   Discussion ..................................................................................................................... 110  

Chapter 3 Fitness Trade-offs Associated with the Evolution of Resistance to Antifungal Drug

Combinations ............................................................................................................................. 119

3 Fitness Trade-offs Associated with the Evolution of Resistance to Antifungal Drug

Combinations ............................................................................................................................. 119

3.1   Introduction .................................................................................................................. 119  

3.2   Materials and Methods ................................................................................................. 122  

3.2.1 Strains and culture conditions ................................................................................ 122

3.2.2 Strain construction ................................................................................................. 126

3.2.3 Plasmids and oligonucleotides ............................................................................... 132

3.2.4 Drug susceptibility assays ...................................................................................... 139

3.2.5 In vitro competition experiments ........................................................................... 140

3.2.6 In vivo competition experiments ............................................................................ 142

3.2.7 Growth rate kinetics ............................................................................................... 143

3.2.8 Filamentation assays .............................................................................................. 143

3.2.9 Cidality spotting assay ........................................................................................... 143

3.3   Results .......................................................................................................................... 144  

3.3.1 In vivo and in vitro evolution of resistance to drug combinations ......................... 144

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3.3.2 Strains with distinct genetic backgrounds resistant to drug combinations are more

fit than ancestral strains in drug combinations .................................................................. 148

3.3.3 The mechanism of resistance in late-stage clinical isolates is largely independent of

Hsp90 and calcineurin, in contrast to some experimentally evolved strains ..................... 151

3.3.4 TAC1A736V, UPC2A643V and ERG11R467K confer Hsp90- and calcineurin-independent

azole resistance in late-stage clinical isolates .................................................................... 155

3.3.5 Resistance to fluconazole and geldanamycin or fluconazole and FK506 is costly in

several host relevant environments .................................................................................... 159

3.3.6 Late-stage clinical isolates are unable to filament in response to geldanamycin due

to TAC1A736V-regulated efflux of geldanamycin ................................................................ 163

3.3.7 Relative fitness is variable in a host model system ................................................ 170

3.4   Discussion ..................................................................................................................... 173  

Chapter 4 Conclusion, general discussion and future directions ............................................... 179

4 Conclusion, general discussion and future directions ......................................................... 179

4.1   Conclusion .................................................................................................................... 179  

4.2   Discussion ..................................................................................................................... 180  

4.2.1 Combination therapy in the treatment of disease ................................................... 180

4.3   Future directions ........................................................................................................... 187  

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List of Tables

Table 2.1. Strains used in this study .................................................................................. 45

Table 2.2. Plasmids used in this study ............................................................................... 57

Table 2.3. Oligonucleotides used in this study .................................................................. 59

Table 2.4. Evolution experiment treatments and conditions ............................................. 65

Table 2.5. Mean coverage whole-genome sequenced strains ............................................ 73

Table 2.6. High confidence single nucleotide variants (coding and non-coding) identified in S.

cerevisiae ........................................................................................................... Separate file

Table 2.7. High confidence single nucleotide variants (coding and non-coding) identified in C.

albicans .............................................................................................................. Separate file

Table 2.8. Non-synonymous S. cerevisiae single nucleotide variants ............................... 95

Table 2.9. Number of high confidence C. albicans single nucleotide variants (SNVs)

(coding and non-coding) .................................................................................................... 97

Table 2.10. Non-synonymous C. albicans single nucleotide variants ............................. 108

Table 3.1. Corresponding strain names between Chapters Two and Three .................... 123

Table 3.2. Strains used in this study ................................................................................ 123

Table 3.3. Plasmids used in this study ............................................................................. 133

Table 3.4. Primers used in this study ............................................................................... 136

Table 3.5. Stressor concentrations for competition and growth rate assays .................... 141

xi

List of Figures

Figure 1.1. Mode of action of azoles and echinocandins and resistance mechanisms ...... 10

Figure 1.2. Studying the evolution of resistance to antifungals ........................................ 28

Figure 2.1. Dose response matrices were used to select concentrations for the evolution

experiment ......................................................................................................................... 68

Figure 2.2. Design and outcome of the experimental evolution of resistance to drug

combinations ...................................................................................................................... 76

Figure 2.3. The populations evolved distinct resistance profiles ....................................... 79

Figure 2.4. Cross-resistance profiles provide a strategy to predict resistance

mechanisms ....................................................................................................................... 83

Figure 2.5. Mutations in HSP90 confer resistance to azole and geldanamycin in two S.

cerevisiae lineages and in one C. albicans lineage ............................................................ 87

Figure 2.6. Ca-G-10 is slightly resistant to azole and geldanamycin, and slightly cross-resistant

to azole and 17-AAG, a structural derivative of geldanamycin ........................................ 89

Figure 2.7. Mutations in FPR1 confer resistance to azole and FK506 in two S. cerevisiae

lineages .............................................................................................................................. 92

Figure 2.8. Whole genome sequencing identifies mutations that confer resistance to azole and

FK506, as well as azole and geldanamycin ....................................................................... 99

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Figure 2.9. Six C. albicans lineages evolved with azole and FK506 share the same cross-

resistance profile, and a mutation in CNA1 and LCB1 confer resistance ........................ 102

Figure 2.10. Aneuploidies identified in four C. albicans lineages that evolved resistance to the

combination of azoles and calcineurin inhibitors ............................................................ 106

Figure 3.1. Lab-passaged strains and late-stage clinical isolates of C. albicans evolved resistance

to drug combinations ....................................................................................................... 147

Figure 3.2. Fitness differences between strains are often reflected in differences in growth rates

......................................................................................................................................... 150

Figure 3.3. Fluconazole resistance of clinical isolates is largely Hsp90- and calcineurin-

independent, in contrast to in vitro evolved strains ......................................................... 154

Figure 3.4. Together, TAC1A736V, UPC2A643V and ERG11R467K confer resistance to fluconazole in

combination with geldanamycin or FK506 ..................................................................... 158

Figure 3.5. Resistance to drug combinations is costly in the absence of drug and in different

stressful environments ..................................................................................................... 162

Figure 3.6. Late-stage clinical isolates do not filament in response to geldanamycin .... 166

Figure 3.7. Genetic background for the in vitro evolved strains has increased susceptibility to

geldanamycin ................................................................................................................... 168

Figure 3.8. TAC1A736V abolishes filamentation in late-stage clinical isolates .................. 170

Figure 3.9. Fitness in a host model is variable ................................................................ 173

xiii

List of Abbreviations

17-AAG 17-allylamino-17-demethoxygeldanamycin

ANOVA analysis of variance

ATP adenosine triphosphate

CsA cyclosporin A

DNA deoxyribonucleic acid

EBI ergosterol biosynthesis inhibitor

FLP flippase recombination enzyme

GdA geldanamycin

GFP green fluorescent protein

Hsp90 heat shock protein 90

MIC minimum inhibitory concentration

MPC mutant prevention concentration

MSW mutant selection window

NAT nourseothricin

OD optical density

PCR polymerase chain reaction

NF-AT nuclear factor of activated T cells

PKC protein kinase C

RAD radicicol

xiv

RNA ribonucleic acid

YPD yeast peptone dextrose

1

Chapter 1 Introduction

1 Introduction

1.1 Evolution of drug resistance in microbes

The evolution of resistance to antimicrobials is a ubiquitous phenomenon. The success of a new

antimicrobial is ultimately undermined by the evolution of resistance that inevitably follows. For

example, resistance to penicillin was found in Gram-positive bacteria a mere six years after its

clinical use was initiated (Barber and Whitehead 1949). Resistance arises rapidly, as evidenced

by the nearly 1000 beta-lactam antibiotic inactivating beta-lactamases that have been identified, a

ten-fold increase since 1990 (Davies and Davies 2010).

Strong selection for resistance is imposed by the widespread deployment of antimicrobials in the

clinic as well as in environmental settings, such as the treatment of crops or livestock with

antimicrobials. With the increase in the immunocompromised population due to infections like

HIV and modern medical breakthroughs like chemotherapy and organ transplantation, the

population of individuals susceptible to infection has increased. This combination of factors

makes antimicrobial resistance one of the most serious threats to public health. Furthermore, the

economic effects of drug resistance are astonishing, as the combined cost of treatment of patients

with drug-resistant infections, pesticide use on crops for the treatment of drug-resistant pests and

crop losses is a minimum of $33 billion USD annually (Palumbi 2001).

Treatment of resistant pathogens is a constant struggle. The arsenal of antimicrobials is

becoming increasingly limited as resistance to multiple drug classes is emerging. The microbes

that pose the greatest risk to public health are now resistant to multiple drug classes, such as the

bacteria Clostridium difficile and drug-resistant Neisseria gonorrhoeae (CDC 2013). The rate at

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which new antimicrobials are being produced is vastly outpaced by the rate at which resistance

emerges. Despite this, fewer new antimicrobials are being developed. Since the 1970’s only one

antibiotic and one antifungal with novel modes of action have reached the clinic (the

oxazolidinones and the echinocandins, respectively) (Norrby, Nord et al. 2005). This may be

partly due to the fact that research and development of new drugs, particularly clinical trials, is

exceedingly expensive and therefore often pursued foremost by pharmaceutical companies.

However, pharmaceutical companies are deterred by lower return per treatment of antimicrobials

relative to developing drugs prescribed for life, such as those used to treat hypertension or

diabetes. Furthermore, the number of novel drug targets is limited, particularly for fungi who

share close evolutionary relationships with their host, ultimately causing host toxicity issues.

Effective stewardship of our antimicrobials is a critical component of the fight against antibiotic

resistance (Laxminarayan, Duse et al. 2013). Making our current arsenal of antimicrobials more

effective is therefore of paramount importance.

In particular, fungal drug resistance is a pressing issue. Antifungal drug resistance is

tremendously costly, in terms of both human mortality (McNeil, Nash et al. 2001) and financial

burden (Dasbach, Davies et al. 2000). The most significant challenge in developing new

antifungals is avoiding host toxicity while effectively killing the pathogen. The close

evolutionary relationship between fungal pathogens and their human hosts limits the number of

fungal-specific drug targets available (Baldauf, Roger et al. 2000). Resistance to antifungals

evolves at a rate faster than new antifungals are being developed. The most commonly used

classes of antifungals, the azoles and the echinocandins, target the biosynthesis of the fungal-

specific cell membrane sterol ergosterol and the fungal cell wall, respectively (Cowen 2008).

These limitations in drug development underscore the importance of determining how drug

resistance evolves in order to predict and prevent it.

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1.2 Candida albicans

Candida albicans is a clinically relevant organism with which to study the evolution of drug

resistance. It is an opportunistic pathogen and the leading cause of death due to mycotic

infection, and the fourth most common cause of nosocomial bloodstream infections (Pfaller and

Diekema 2007). C. albicans is found as a commensal on 15 – 60% of asymptomatic individuals,

where is it able to reside in diverse niches such as the oral cavity and the gastrointestinal tract

(Odds, Gow et al. 2001). In immunocompetent hosts, it causes superficial infections in moist

areas (typically the groin and toe webs), however, upon impairment of the host immune system,

C. albicans is able to penetrate tissues to cause serious invasive fungal infections of the blood,

normally sterile body fluids, and of deep tissue and organs (Horn, Neofytos et al. 2009; Marr

2010; Pfaller and Diekema 2010). Thus, immunocompromised individuals and those hospitalized

with serious underlying diseases, such as stem cell transplant recipients, solid organ transplant

recipients, those undergoing major surgery, those undergoing chemotherapy, those infected with

HIV, neonatal infants and those of advanced age, are particularly susceptible to invasive C.

albicans infection (Pfaller and Diekema 2010). Due to advances in medical technology, the

immunocompromised population has increased, which has lead to a 207% increase in

bloodstream infections caused by fungal pathogens between 1979 and 2000 in the United States

(Martin, Mannino et al. 2003).

A key feature of C. albicans virulence is its ability to undergo morphogenesis. C. albicans is

polymorphic, existing as yeast or in its pseudohyphal or hyphal filamentous forms. It is thought

that the ability to penetrate tissues and cause deep-seated infection requires filamentous growth,

while bloodstream dissemination to target organs requires yeast form growth (Saville, Lazzell et

al. 2003). Indeed, several studies have indicated that mutants locked in either morphology are

4

attenuated in virulence (Shapiro, Robbins et al. 2011). The ability to undergo morphogenesis also

facilitates survival in the host, as macrophage killing by C. albicans is associated with the ability

to transition between morphologies (McKenzie, Koser et al. 2010). The ability to undergo

morphogenesis is essential to the lifestyle of C. albicans.

Candida albicans exhibits a high level of genomic plasticity. Widespread aneuploidy in lab

strains was discovered by comparative genomic hybridization, and this aneuploidy occurred

more frequently in strains exposed to stressors like the process of transformation and

counterselection on 5-fluoro-orotic acid (Selmecki, Bergmann et al. 2005). It has recently been

shown that exposure to the antifungal fluconazole also induces aneuploidy (Harrison, Hashemi et

al. 2014). This evidence suggests that aneuploidy can be adaptive, and indeed this has been

demonstrated by the formation of an isochromosome of the left arm of chromosome 5 in

response to fluconazole exposure. This isochromosome contained extra copies of a

transcriptional activator of drug efflux pumps (TAC1) and the drug target itself, ERG11

(Selmecki, Forche et al. 2006). Furthermore, the stress of passage through a host model system

induced more large-scale genomic rearrangements than passage in test tubes (Forche, Magee et

al. 2009). This remarkable genome lability enhances the ability of C. albicans to cope with a

broad spectrum of stressors.

Genomic flexibility, lack of meiotic cycle and inability to maintain plasmids can render

molecular studies with C. albicans challenging (Berman and Sudbery 2002). It is advantageous,

therefore, to perform complementary experiments with its genetically tractable relative,

Saccharomyces cerevisiae, with whom it often shares drug resistance phenotypes and underlying

molecular mechanisms (Cowen and Steinbach 2008). Tools for study with S. cerevisiae are

greater in number and more developed. S. cerevisiae supports plasmids, has a complete sexual

5

cycle, and has more efficient homologous recombination. Complementary studies in S.

cerevisiae can provide insights into drug resistance mechanisms relevant to C. albicans.

1.3 Antifungal drugs

1.3.1 Major antifungal drugs and their mode of action

The number of fungal-specific drug targets is limited due to conservation with the human host.

The majority of antifungals that are clinically deployed target the fungal-specific sterol

ergosterol, or its biosynthesis, or the fungal cell wall (Cowen 2008; Shapiro, Robbins et al.

2011). The utility of these antifungals is compromised by their often fungistatic

(antiproliferative) nature. Reservoirs of cells tolerant to fungistatic drugs are poised for the

evolution of resistance. This section will focus on antifungals currently available for the

treatment of the most prevalent fungal infections.

1.3.1.1 Azoles

The most widely deployed class of antifungals, the azoles, are ergosterol biosynthesis inhibitors

(EBIs). EBIs are a large class of antifungals that function by targeting enzymes involved in the

biosynthesis of ergosterol, the bulk sterol of fungal membranes that is involved in maintaining

membrane fluidity and cellular signal. Ergosterol is the fungal equivalent of cholesterol

(Anderson 2005). Ergosterol is synthesized from squalene; the genes in this pathway encode

products that act in the following order: Erg1, Erg7, Erg11, Erg24, Erg25, Erg26, Erg27, Erg6,

Erg2, Erg3, Erg5 and Erg4 (White, Marr et al. 1998).

Azoles have been clinically deployed for almost 30 years. They inhibit fungal growth by binding

to the P450 enzyme α-14-lanosterol demethylase (encoded by ERG11), a late-stage enzyme in

the ergosterol biosynthesis pathway. Inhibition of ERG11 blocks the production of ergosterol and

leads to the accumulation of methylated sterol intermediates in the cell membrane, which alters

6

membrane fluidity and inhibits growth (Cowen 2008). Inhibition of ERG11 also reduces the

overall amount of ergosterol in the cell, thus interfering with vacuolar H+-ATPase activity, which

is necessary for ion homeostasis and fungal virulence (Zhang, Gamarra et al. 2010).

Azoles are classified into two groups, the imidazoles and newer triazoles. Imidazoles suffer from

toxicity and bioavailability issues and are only available in topical, over-the-counter formulations

for vaginal or skin infections (Ostrosky-Zeichner, Casadevall et al. 2010). Triazoles must be

prescribed and are available in oral or injection formats, and are used in the treatment of systemic

fungal infections. The four triazoles currently available clinically are fluconazole, itraconazole,

posaconazole and voriconazole. Azoles are effective for treating diverse fungi, including species

of Candida, Cryptococcus, and Aspergillus, as well as dimorphic and dermatophyte fungi

(Shapiro, Robbins et al. 2011). Posaconazole is also effective against zygomycete fungi

(Alastruey-Izquierdo, Castelli et al. 2009). However, azoles are fungistatic against yeasts like

Candida, such that strong selective pressure for resistance is imposed upon tolerant cells

(Anderson 2005). Clinical resistance in yeasts is a significant clinical issue.

1.3.1.2 Echinocandins

The newest class of antifungals is the echinocandins. These drugs disrupt cell wall biosynthesis

by inhibiting the enzyme β-(1,3)-glucan synthase, the subunits of which are encoded by FKS1

and FKS2 (Cowen and Steinbach 2008). This results in a loss of cell wall integrity. The

echinocandins are broadly effective against many fungi including Candida and Aspergillus

species, but not against Cryptococcus or zygomycetes. Unlike azoles, echinocandins are

generally fungicidal against yeasts and resistance is not yet widespread, although numerous

clinical isolates with elevated resistance have been identified (Shapiro, Robbins et al. 2011). The

7

echinocandins have little to no toxicity to the host, and, because they are fungicidal, they are

becoming the drug of choice for treatment of invasive fungal infections.

1.3.1.3 Polyenes

The polyenes have been used in the clinic for the past 50 years. They bind to ergosterol in fungal

cell membranes, resulting in the formation of pores that allow small molecules like ions to

diffuse across the membrane, ultimately resulting in cell death (White, Marr et al. 1998). The

most commonly deployed polyenes are amphotericin B and nystatin. Amphotericin B is effective

against Candida, Cryptococcus and Aspergillus infections and was previously considered the

gold standard for treatment of invasive fungal infections; it is highly insoluble and is typically

delivered in liposomal formulations to increase solubility when given intravenously. Therapeutic

use of amphotericin B is complicated by significant liver toxicity, poor pharmacokinetics and

other side effects like fevers and tremors (Paterson, Seaton et al. 2003). As such, it is not

typically used to treat chronic fungal infections or for prophylaxis and is now considered a third-

line defense. Nystatin is also nephrotoxic and highly insoluble; it is typically given only in

lozenge format to treat oropharyngeal candidiasis. Resistance to polyenes is not widespread, such

that a recent survey of over 9000 clinical isolates found that 99.8% were sensitive to

amphotericin B (Pfaller, Espinel-Ingroff et al. 2012). This is in part due to their limited use and

fungicidal nature, but also due to the high fitness cost resistance incurs (Vincent, Lancaster et al.

2013). The best-characterized resistance mechanism is concurrent loss of function of ERG11 and

ERG3, both members of the ergosterol biosynthesis pathway (Sanglard, Ischer et al. 2003).

1.3.1.4 Other antifungals

Other than the azoles, commonly used classes of EBIs are the allylamines and morpholines. The

allylamines, including terbinafine, and the thiocarbamates, including tolnaftate, act by inhibiting

8

Erg1; they are available in over-the-counter topical preparations. In contrast, morpholines such

as fenpropimorph are commonly used in agricultural settings to target fungal pathogens of plants

(Zocco, Van Aarle et al. 2011). Morpholines target two enzymes in the ergosterol biosynthetic

pathway, C-8 sterol isomerase (encoded by ERG2) and C-14 sterol reductase (encoded by

ERG24).

There are several other antifungals that are clinically employed or currently in development. The

classic antifungal 5-flucytosine inhibits fungal nucleic acid biosynthesis, but its effect is

fungistatic and resistance develops readily (White, Marr et al. 1998). 5-flucytosine is therefore

typically only used in combination with other antifungals. Emerging antifungals include

sordarins and nikkomycin Z. Sordarins are semi-synthetic natural products that had shown

antifungal activity as early as the 1970’s (Ostrosky-Zeichner, Casadevall et al. 2010). They

function as antifungals by inhibiting fungal elongation factor 2 during protein biosynthesis. The

sordarin derivative FR290581 has demonstrated robust antifungal activity against C. albicans

and is currently in development. Nikkomycin Z interferes with cell wall biosynthesis by

competitively inhibiting chitin synthases. Phase I clinical trials of nikkomycin Z are currently

underway (Ostrosky-Zeichner, Casadevall et al. 2010).

1.3.2 Drug resistance mechanisms

Acquired resistance to antifungals can occur through several mechanisms. The canonical

resistance mechanisms are drug target alteration or overexpression, reduction of intracellular

drug accumulation, and upregulation of stress response pathways (Figure 1.1). These resistance

mechanisms need not occur in isolation; in fact clinical isolates frequently exhibit several

mechanisms of resistance. This section focuses on genetically stable resistance mechanisms.

9

10

Figure 1.1. Mode of action of azoles and echinocandins and resistance mechanisms. A)

Azoles enter the cell by facilitated diffusion and inhibit Erg11, blocking the production of

ergosterol and resulting in the accumulation of a toxic sterol intermediate, which results in cell

membrane stress. Resistance to azoles can arise by: B) upregulation of two classes of efflux

pumps that remove the drug from the cell; C) mutation or overexpression of ERG11, which

minimizes the impact of the drug on the target; or D) loss-of-function mutation of ERG3, which

blocks the accumulation of a toxic sterol that is otherwise produced when Erg11 is inhibited by

azoles. E) Echinocandins inhibit β-(1,3)-glucan synthase (the catalytic subunit is encoded by

FKS1 and FKS2 in S. cerevisiae), and thus disrupt cell wall integrity. F) Resistance to

echinocandins can arise by mutations in FKS1 or FKS2 that minimize the impact of the drug on

the target.

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1.3.2.1 Alteration of drug target

The most direct mechanism to increase resistance to an antimicrobial is by mutation of the drug

target that reduces drug binding. One example of this is alteration of ERG11 encoding the azole

target enzyme in C. albicans. In a well-characterized series of matched susceptible and resistant

isolates, an R467K amino acid substitution was identified that conferred azole resistance (White

1997). This mutation reduces the susceptibility of the enzyme to azoles, likely through

decreasing the azole binding affinity (Lamb, Kelly et al. 2000). Numerous other ERG11

mutations have been identified within several mutational ‘hot spots’ that result in amino acid

substitutions that are in or adjacent to the active site. Elevated resistance is often associated with

subsequent loss of heterozygosity that results in two mutated alleles of the gene.

Echinocandin resistance also occurs by target alteration. In echinocandin-resistant isolates of C.

albicans, mutations in the target genes FKS1 and FKS2 (also referred to as GSL1 and GSC1)

have been found, leading to alteration of the glucan synthase (Munro 2010). Similar mutations in

FKS1 and FKS2 contributing to echinocandin resistance have been identified in C. glabrata

(Zimbeck, Iqbal et al. 2010). Elevated echinocandin resistance in C. albicans has been associated

with loss of heterozygosity of FKS1, leaving two mutant alleles, as with ERG11 and azole

resistance (Niimi, Monk et al. 2010).

1.3.2.2 Overexpression of drug target

Increased expression of the drug target can also confer resistance. For example, overexpression

of ERG11 has been documented in azole-resistant C. albicans clinical isolates. ERG11

overexpression can occur by gain-of-function mutations in the transcriptional activator encoded

by UPC2, leading to overexpression of ergosterol biosynthesis genes including ERG11 (Dunkel,

Liu et al. 2008; Hoot, Smith et al. 2011). Multiple studies identified mutations in the same C-

12

terminal region of UPC2 in azole-resistant C. albicans clinical isolates (Dunkel, Liu et al. 2008;

Heilmann, Schneider et al. 2010; Hoot, Smith et al. 2011). In a clinical isolate containing UPC2

A643T, loss of heterozygosity occurred rendering the mutation homozygous and further

elevating resistance. That these amino acid substitutions in diverse isolates arise in a restricted

region of the protein suggests that this region has an essential regulatory function.

Recently, two UPC2 homologs were identified in C. glabrata that, like in C. albicans, regulate

the response to azoles and hypoxia (Nagi, Nakayama et al. 2011). However, UPC2 homologs are

limited to these and related species. In other ascomycetes and in basidiomycetes such as C.

neoformans, ergosterol biosynthesis is regulated at the transcriptional level by an SREBP-like

transcription factor Sre1 (Bien and Espenshade 2010). This protein has functional homology to

the mammalian cholesterol regulatory transcription factor SREBP. In A. fumigatus, a similar

SREBP homolog called SrbA regulates sterol biosynthesis (Willger, Puttikamonkul et al. 2008).

These species also contain homologs of some of the other proteins that regulate the SREBP

pathway, such as the proteases or chaperones involved in regulating SREBP proteolytic cleavage

(Bien and Espenshade 2010). In both C. neoformans and A. fumigatus, the SREBP-like proteins

are required for sterol regulation in response to hypoxia and antifungal drugs, and are also

implicated in virulence in animal models.

1.3.2.3 Increased drug efflux

Reduction of intracellular drug concentration by active drug efflux can also lead to antifungal

drug resistance, especially for the azoles, and is well studied in C. albicans (White, Marr et al.

1998). In C. albicans, azole efflux is mediated by overexpression of the ATP-dependent pumps

Cdr1 and Cdr2, or the major facilitator pump Mdr1. Tac1 is the central transcriptional activator

of CDR1 and CDR2 expression in C. albicans. TAC1 gain-of-function mutations have been

13

identified and are often homozygous in CDR1 overexpressing clinical isolates (Coste, Karababa

et al. 2004; Coste, Turner et al. 2006). Another C. albicans transcription factor, Ndt80 has been

implicated in CDR1 transcriptional activation (Wang, Yang et al. 2006). Interestingly, CDR2

overexpression can confer a slight decrease in susceptibility to echinocandins, however, only on

solid agar media (Schuetzer-Muehlbauer, Willinger et al. 2003; Silver, Oliver et al. 2008). The

major transcriptional activator of MDR1 expression in C. albicans is Mrr1; MRR1 mutations can

lead to overexpression of MDR1 (Dunkel, Liu et al. 2008). However, unlike Upc2, neither Tac1

nor Mrr1 are activated in response to azoles.

Increased efflux of antifungals is a major mechanism of resistance in other fungal pathogens as

well. In C. neoformans, overexpression of the efflux pumps encoded by AFR1 and MDR1

confers a decrease in azole susceptibility (Sionov, Lee et al. 2010). A. fumigatus also encodes a

major facilitator gene MDR1, but expression of this gene in S. cerevisiae does not impart

resistance to azoles, but only to the drug cilofungin, which is not used clinically (Morschhauser

2010). An ABC transporter encoding gene in A. fumigatus, atrF, was shown to be induced at the

transcriptional level by azoles, and overexpression of this gene was correlated with azole

resistance (Morschhauser 2010).

1.3.2.4 Genome plasticity

Aneuploidy can facilitate increased resistance to antifungals. While aneuploidy itself is not

known to confer resistance, the increased dosage of specific genes on an extra chromosome can

contribute to resistance. In C. albicans clinical isolates, evidence of genomic plasticity

contributing to resistance is well documented. A survey of 70 azole-resistant and susceptible

isolates revealed that resistant isolates had a preponderance of aneuploidies, the most common of

which involved chromosome 5, often with duplications of the left chromosome arm.

14

Recombination events occurring at a common breakpoint in repetitive sequences flanking the

centromere led to production of an isochromosome with two left arms of chromosome 5, termed

i(5L) (Selmecki, Forche et al. 2006). Functional analyses confirmed that in i(5L) containing

strains, azole resistance is due to duplication of both ERG11 and TAC1 alleles that reside on the

left arm of chromosome 5 (Selmecki, Gerami-Nejad et al. 2008). C. neoformans also adapts to

azoles by duplication of specific chromosomes, including chromosome 1, which harbors ERG11

as well as the major azole transporter gene AFR1 (Sionov, Lee et al. 2010).

1.3.2.5 Upregulation of stress response pathways

Stress response pathways play a critical role in mediating both basal tolerance and resistance to

diverse antifungals. For example, the molecular chaperone Hsp90 regulates crucial responses to

both azoles and echinocandins in diverse fungi (Cowen and Lindquist 2005; Cowen 2008;

Cowen 2009; Singh, Robbins et al. 2009). In C. albicans, Hsp90 regulates drug resistance by

stabilizing key regulators of cellular stress responses, including the protein phosphatase

calcineurin and the terminal mitogen activated protein kinase in the Pkc1 cell wall integrity

signaling pathway, Mkc1 (Singh, Robbins et al. 2009; LaFayette, Collins et al. 2010). The cell

wall integrity pathway regulates not only resistance to drugs that target the cell wall, but also

resistance to drugs that target the cell membrane (LaFayette, Collins et al. 2010). Drugs that

inhibit Hsp90, calcineurin, or Pkc1 reduce azole and echinocandin resistance of isolates that

evolved resistance in a human host (Cruz, Goldstein et al. 2002; Singh, Robbins et al. 2009;

LaFayette, Collins et al. 2010). While upregulation of stress response pathways has not yet been

identified as a resistance mechanism, it is clear that these signaling pathways are key components

of the cellular circuitry regulating drug resistance.

15

1.4 Strategies for thwarting the evolution of drug resistance

1.4.1 Developing new antifungals

There are relatively few drugs available to treat fungal infections and resistance to these

antifungals has had a significant clinical impact, such that the development of new antifungals

will be essential to keep the upper hand in the battle against these pervasive pathogens.

Generally, new antifungals have an average of ten years after the start of clinical use before

resistance becomes common. This necessitates the perpetual identification of new drug targets

and small molecules to inhibit those targets.

The development of new antifungals is complicated by the evolutionary relatedness of these

eukaryotic pathogens to humans. To avoid host toxicity, differences between fungi and humans

must be exploited to develop new drugs; however, new targets remain somewhat elusive. One set

of candidates is the fungal-specific zinc cluster transcription factors, many of which regulate

aspects of fungal drug resistance (such as Upc2, Tac1 and Mrr1). Efforts to identify drugs that

inhibit these proteins have not yet been successful. The search for new fungal-specific drug

targets will be an ongoing area of research for the control of fungal infections.

1.4.2 Combination therapy

Combination therapies have long been known to be potentially more effective than single drug

therapy at limiting the development of resistance. Typically, combination therapy employs two

antifungals that target more than one pathway (White, Marr et al. 1998). The synergistic effect of

appropriately selected antifungals in combination will more substantially reduce the fungal

population size, therefore reducing the genetic space over which mutations can arise.

Furthermore, in order for resistance to occur, mutations would need to arise that permit fungal

growth in the presence of both drugs.

16

One example of combination therapy is the use of 5-flucytosine and amphotericin B to treat

fungal infections. This drug combination is commonly used in the treatment of cryptococcal

meningitis (Bennett, Dismukes et al. 1979). Resistance to 5-flucytosine develops readily, but its

effectiveness can be prolonged when used in combination with amphotericin B (White, Marr et

al. 1998). This combination therapy is complicated, however, due to the nephrotoxicity of

amphotericin B. Notably, 5-flucytosine can also be used in combination with azole therapy.

Other combinations that show promise in vitro and in animal models are Hsp90 inhibitors with

azoles or echinocandins in the treatment of C. albicans or A. fumigatus infections (Cowen, Singh

et al. 2009). As with Hsp90 inhibitors, calcineurin inhibitors enhance antifungal efficacy and

block the emergence of drug resistance, motivating the search for non-immunosuppressive

agents that retain antifungal activity (Steinbach, Cramer et al. 2007).

1.4.3 Targeting stress response: Hsp90 and calcineurin

Traditional antifungals target fungal pathways required for proliferation or viability. Recent work

has focused on inhibiting cellular factors that are required for the evolution of resistance but do

not directly confer resistance. The molecular chaperone Hsp90 and its client protein calcineurin

have been shown to be required for resistance or tolerance to echinocandins and azoles in

Candida and Aspergillus species, as previously described in this chapter. Other regulators of

fungal drug resistance exist: the protein kinase C (PKC) signaling pathway has been identified as

regulator of fungal stress response such that with deletion of PKC1 in C. albicans or S.

cerevisiae, resistance to azoles is abrogated (LaFayette, Collins et al. 2010). Here I focus on the

regulators relevant to my work, Hsp90 and calcineurin.

17

1.4.3.1 Hsp90

Hsp90 is a fascinating, highly abundant, essential protein in eukaryotes. As a molecular

chaperone, it facilitates the folding of its meta-stable client proteins, helping prevent aggregation

in the crowded environment of the cytoplasm under basal conditions (Taipale, Jarosz et al. 2010).

Under proteotoxic stress conditions, such as high temperature, or exposure to heavy metals,

hypoxia and acidosis, Hsp90 expression levels are increased in an effort to maintain protein

homeostasis in a hostile environment (Whitesell and Lindquist 2005). Its clients are diverse but

tend to be regulatory hubs, such as kinases and transcription factors. The factors that determine

what make a protein an Hsp90 client had remained elusive until recently, when it was determined

that thermal instability of a protein dictated its association with Hsp90 (Taipale, Krykbaeva et al.

2012). It has been estimated that Hsp90 interacts with ~10% of the proteome in S. cerevisiae, and

has comparably extensive interactions in C. albicans (Zhao, Davey et al. 2005; Diezmann,

Michaut et al. 2012).

Hsp90 is a highly conserved protein. It is composed of N-terminal, middle and C-terminal

domains and functions as a homodimer, dimerizing at the C-terminal domain (Whitesell and

Lindquist 2005). The flexible middle domain is thought to be important for client protein

recognition, with the assistance of co-chaperones (Meyer, Prodromou et al. 2003). The N-

terminal domain contains a site that binds to and hydrolyzes ATP as a requirement of Hsp90

function. This nucleotide-binding pocket contains an unusual Bergerat fold, making it distinct

from other ATPases (Dutta and Inouye 2000). Several Hsp90 inhibitors, including geldanamycin

(GdA) and radicicol (RAD), competitively inhibit the binding of ATP to this nucleotide-binding

pocket, which blocks Hsp90 function (Stebbins, Russo et al. 1997; Whitesell and Lindquist

2005).

18

A fascinating aspect of Hsp90’s biology is its role as both a phenotypic capacitor and a

phenotypic potentiator. Landmark studies in Drosophila melanogaster and Arabidopsis thaliana

demonstrated that Hsp90 buffered underlying genetic variation that was exposed upon Hsp90

depletion, demonstrating its role as a capacitor (Rutherford and Lindquist 1998; Queitsch,

Sangster et al. 2002). Recently, it has been demonstrated that Hsp90 acts as a capacitor for eye

morphology variation in surface populations of cavefish, whose cave-dwelling conspecifics lose

their eyes. Raising surface populations of cavefish in cave conditions unmasks underlying

genetic variation, similar to Hsp90 depletion, suggesting that Hsp90 plays a role in canalizing

eye morphology (Rohner, Jarosz et al. 2013). Hsp90’s role as a phenotypic potentiator is

exemplified by resistance to azoles and echinocandins in diverse fungi (Cowen 2013). A

systematic study assayed the phenotypes upon Hsp90 inhibition of a diverse set of 102 S.

cerevisiae strains, and found that Hsp90 worked as a phenotypic capacitor as frequently as a

phenotypic potentiator (Jarosz and Lindquist 2010). In cancer cells, Hsp90’s physiological

protein stabilizing activity is subverted to chaperone proteins that have become destabilized by

oncogenic promoting mutations (Whitesell and Lindquist 2005). Hsp90 inhibitors, such as

derivatives of GdA, are in clinical development as anti-cancer agents.

Hsp90 inhibitors have recently been tested to assess their utility in combination therapy with

azoles or echinocandins in the wax moth G. mellonella and mouse models of infection (Cowen,

Singh et al. 2009). While effective at enhancing the efficacy of antifungals in the wax moth

larval model of infection, toxicity to the mouse in the context of an acute fungal infection

compromised the therapeutic utility although in a biofilm rat catheter model, there was no

toxicity when the drug delivery and fungal infection were localized (Robbins, Uppuluri et al.

2011). For systemic infections, fungal-specific Hsp90 inhibitors would therefore be an extremely

valuable tool to prevent the development of resistance in vivo and extend the clinical usefulness

19

of antifungal drugs. Hsp90 holds great promise as a therapeutic target for extending the clinical

efficacy of existing drugs to which antifungal resistance has already been documented.

1.4.3.2 Calcineurin

Calcineurin is a Ca+-activated, serine/threonine phosphatase that plays a crucial role in cellular

stress response, from yeast to humans (Fox and Heitman 2002). In diverse fungi, it has roles in

several critical cellular processes, including drug resistance, morphogenesis, virulence, cell cycle

progression and ion homeostasis (Shapiro, Robbins et al. 2011). In humans, it is implicated in

many critical developmental and cellular processes, most notably in immune response by

dephosphorylation of the cytoplasmic component of the nuclear factor of activated T cells (NF-

AT), which leads to transcriptional activation of IL-2 and T cell activation (Steinbach, Reedy et

al. 2007).

Calcineurin is a heterodimer, composed of a catalytic subunit and a regulatory subunit. Upon the

release of calcium stores, Ca+-calmodulin binds to the catalytic subunit, which displaces its

autoinhibitory domain and exposes its active site (Fox and Heitman 2002). The catalytic subunit

of calcineurin is stabilized by Hsp90 in both C. albicans and S. cerevisiae (Imai and Yahara

2000; Singh, Robbins et al. 2009). Activity of calcineurin also requires the association of the

catalytic subunit with the regulatory subunit; mutant regulatory subunits unable to bind to the

catalytic subunit abolish calcineurin activity (Watanabe, Perrino et al. 1996).

The immune response controlled by calcineurin has distinguished it as a target for

immunosuppressive drugs. FK506 and cyclosporin A are calcineurin inhibitors exploited for

their inhibitory effect on T cell activation in humans. These drugs have a distinctive method of

calcineurin inhibition: they bind to the peptidyl-prolyl isomerases Fpr1 and Cpr1 (for FK506 and

CsA, respectively) and these drug-protein complexes bind to the hydrophobic interface between

20

the catalytic and regulatory subunits (Fox and Heitman 2002). Because neither of these drug-

protein complexes block the active site, inhibition is thought to occur by occlusion of protein

substrates. The regions to which FK506-Fpr1 and CsA-Cpr1 bind are distinct but overlapping

(Huai, Kim et al. 2002). This inhibition of calcineurin by FK506 and CsA is also conserved

between S. cerevisiae, C. albicans and humans.

1.5 Natural variation in resistance to antifungal drugs

Fungal pathogens are comprised of diverse members of the fungal kingdom. Variation in

response to antifungals exists between both distantly and closely related species, as well as

between strains within a species and even between cells within a single strain. Pathogens can

differ in their inherent ability to survive and reproduce despite the detrimental presence of drug,

often referred to as tolerance. Pathogens can also acquire specific mechanisms that reduce the

inhibitory effect of the drug, referred to as resistance. High levels of basal tolerance can enable

the evolution of resistance by maintaining viability in the context of strong selective pressure.

The vast differences among species and strains in response to specific antifungals highlights the

importance of selecting the appropriate antifungal to administer during clinical treatment.

This section will discuss the differences in resistance and tolerance between and within the major

pathogenic fungal species. Differences in resistance within a species will be covered and special

phenotypic states conferring elevated resistance will be examined.

1.5.1 Variation between species

The major pathogenic fungi, Candida species, Aspergillus fumigatus and Cryptococcus

neoformans, are very distantly related and vary dramatically in their ability to tolerate and

acquire resistance to antifungals (Cowen 2008; Shapiro, Robbins et al. 2011). For example,

fluconazole is one of the most frequently deployed antifungals in treating Candida infections, yet

21

it is completely ineffective against A. fumigatus (Marichal and Vanden Bossche 1995). While

much remains to be understood about its intrinsic tolerance, A. fumigatus can be rendered

susceptible to azoles by deletion of the transcriptional regulator of sterol production, srbA

(Willger, Puttikamonkul et al. 2008). A. fumigatus is susceptible to other azoles, such as

itraconazole and posaconazole (Pfaller and Diekema 2010). Tolerance to azoles in A. fumigatus

can be abrogated by the addition of an inhibitor of Hsp90 or calcineurin (Cowen, Singh et al.

2009). While C. neoformans is inherently susceptible to azoles, it shows remarkable tolerance to

the echinocandins (Abruzzo, Griffith et al. 1997; Krishnarao and Galgiani 1997). How C.

neoformans is able to tolerate echinocandin concentrations that are typically inhibitory is unclear,

although it is known that C. neoformans β-(1,3)-glucan synthase (the echinocandin target) is

inhibited by echinocandins (Thompson, Douglas et al. 1999). Echinocandin tolerance in C.

neoformans is abrogated by inhibition of calcineurin (Del Poeta, Cruz et al. 2000). The

echinocandins are fungicidal against C. albicans and fungistatic against A. fumigatus (Denning

2003).

Variation in tolerance also occurs between closely related fungal pathogens. Candida krusei and

Candida glabrata, for example, have lower intrinsic susceptibility to fluconazole (Blot, Janssens

et al. 2006). In C. krusei, this is mainly due to a low affinity for Erg11 (the target of azoles)

(Lamping, Ranchod et al. 2009). Other azoles, however, can be effective in the treatment of C.

krusei infection (Hoffman, Ernst et al. 2000). A recent study assaying the epidemiological cutoff

value of voriconazole for over 16,000 strains of Candida species found reduced susceptibility in

C. guilliermondii, C. glabrata and C. krusei and greater susceptibility in C. albicans, C.

tropicalis, C. parapsilosis, C. kefyr and C. lusitaniae (Pfaller, Espinel-Ingroff et al. 2012). Unlike

other Candida species, C. lusitaniae and C. guilliermondii are intrinsically resistant to

amphotericin B. Candida species also vary in their sensitivity to echinocandins. C. parapsilosis,

22

for example, shows greater intrinsic resistance to caspofungin and its incidence in the clinic

increases with the application of caspofungin to treat candidemia, while incidence of the more

susceptible C. glabrata and C. tropicalis decrease (Forrest, Weekes et al. 2008; Arendrup,

Rodriguez-Tudela et al. 2011).

Variation exists between Aspergillus species in their susceptibility to the polyene amphotericin

B. Testing hundreds of clinical and environmental Aspergillus isolates revealed higher levels of

amphotericin B tolerance in Aspergillus flavus and Aspergillus terreus, while A. fumigatus and

Aspergillus glaucus were more susceptible (Araujo, Pina-Vaz et al. 2007). It has been speculated

that the intrinsic amphotericin B resistance of A. terreus is due to increased catalase production,

which limits oxidative damage (Blum, Perkhofer et al. 2008). Additionally, most Aspergillus

species are susceptible to echinocandins, but there is reduced susceptibility in select A. nidulans

isolates (Araujo, Pina-Vaz et al. 2007).

The mechanisms of resistance an organism acquires are influenced by the genetic architecture of

tolerance. While most fungal pathogens ultimately evolve antifungal resistance by several

mechanisms, the most prevalent mechanisms may vary between species whose intrinsic

resistance varies. For example, resistance of A. fumigatus to azoles is often due to alteration in

the drug target, cyp51A, the A. fumigatus equivalent of ERG11 (Balashov, Gardiner et al. 2005).

C. neoformans infrequently evolves resistance to azoles, and does so largely by increased azole

efflux or alteration in the drug target (Venkateswarlu, Taylor et al. 1997; Pfaller, Messer et al.

2005), or via heteroresistance and aneuploidy for chromosome 1 (Sionov, Lee et al. 2010).

Similarly, increased azole efflux and target alteration are common mechanisms of azole

resistance in C. albicans (Shapiro, Robbins et al. 2011). With respect to echinocandins, the most

frequently encountered resistance mechanism in C. albicans clinical isolates is mutation in the

23

drug target gene, FKS1 (Park and Morschhauser 2005). However, A. fumigatus echinocandin

resistance is mostly facilitated through stress response pathways and rarely by FKS1 mutations

(Gardiner, Souteropoulos et al. 2005).

Mechanisms of resistance can vary between closely related species as well, like the model yeast

Saccharomyces cerevisiae and C. glabrata, which is more closely related to S. cerevisiae than to

other Candida species. S. cerevisiae is able to acquire fluconazole resistance with the addition of

exogenous ergosterol by importing the sterol (Kuo, Tan et al. 2010). However, C. glabrata lacks

sterol import genes and typically becomes fluconazole resistant by increased efflux (Kuo, Tan et

al. 2010).

1.5.2 Variation between strains

Natural variation within a species can account for differing levels of tolerance among strains. For

example, erg3∆-mediated azole resistance in S. cerevisiae varies between strains W303 and

BY4741/2 in its dependence on downstream effectors of calcineurin, Crz1, Hph1 and Hph2, in a

manner that is dependent on nutrient signaling (Cowen, Carpenter et al. 2006; Robbins, Collins

et al. 2010).

Clinically isolated Candida species have a broad diversity of genotypes. Four major clades of C.

albicans strains have been identified by multilocus sequence typing and DNA fingerprinting

(Odds, Bougnoux et al. 2007; MacCallum, Castillo et al. 2009). Nearly all 5-flucytosine-resistant

samples are members of the first clade, which has acquired a mutation that confers resistance

(Tavanti, Davidson et al. 2005). Likewise, one C. dubliniensis clade has been associated with 5-

flucytosine resistance (Al Mosaid, Sullivan et al. 2005). Members of the C. albicans fourth clade

demonstrate increased tolerance to amphotericin B (Blignaut, Molepo et al. 2005). However, no

correlation between azole resistance and multilocus genotype was found in a set of C. albicans

24

clinical isolates, indicating that the azole resistance was too transient to become associated with a

neutral marker (Cowen, Sirjusingh et al. 1999). Similarly, five C. glabrata clades have been

identified and the isolates with the highest levels of azole resistance were distributed across

clades (Dodgson, Pujol et al. 2003). Very little is known about the impact of population structure

on resistance in the major fungal pathogens besides Candida species.

1.5.3 Variation within a population

Variation in antifungal resistance occurs not only between and within fungal species, but also

within a population of cells. Unlike the predominantly stable variation in resistance found

between strains and species, variation with a population of cells is often more transient.

Heteroresistance is an intriguing example of variation in azole resistance in C. neoformans that is

commonly documented in clinical isolates and in both serotypes A and D, as well as in C. gattii

(Sionov, Chang et al. 2009). Heteroresistance is defined as the emergence of a subset of azole-

resistant cells in addition to azole-susceptible cells from a susceptible progenitor. This

subpopulation gains azole resistance in a stepwise manner and loses this resistance with extended

passage in azole-free media (Sionov, Chang et al. 2009). Recently, comparative genomic

hybridization experiments determined that the azole-resistant cells are disomic, most commonly

for chromosome 1 (Sionov, Lee et al. 2010). The duplicated chromosomes contain genes

important for resistance, such as the azole target ERG11 and azole transporter AFR1, and azole

resistance was shown to correlate with the number of disomic chromosomes. Heteroresistance is

also observed in strains of C. albicans (Marr, Lyons et al. 2001).

There are several other distinct ways in which variation in resistance within a population has

been described. Heterogeneous resistance is a broad term for a phenomenon in fungi and

bacteria, which involves subpopulations of resistant cells that emerge at a low frequency (10-1 to

25

10-4) from a larger susceptible population; colonies formed by the resistant cells again give rise

to the same distribution with only a few resistant cells among a larger susceptible population

(Martinez, Lopez-Ribot et al. 2002). Another related phenomenon is high frequency azole

resistance in which some strains produce azole-resistant colonies at a frequency that is higher

than a typical mutation rate (Martinez, Lopez-Ribot et al. 2002). In contrast to heterogeneous

resistance, the resistant colonies that emerge in the high frequency azole resistance context have

stable resistance phenotypes and it is thought that altered mitochondrial function might play a

role in this phenomenon.

Biofilms are a clinically important example of heterogeneity in drug resistance. Fungal biofilms

are complex surface-associated communities surrounded by an extracellular matrix (Blankenship

and Mitchell 2006). Besides having important virulence implications, biofilms demonstrate a

level of antifungal resistance that is unprecedented in planktonic cells. C. neoformans biofilms,

for example, have significantly higher resistance to amphotericin B and the echinocandin

caspofungin than planktonic cells (Martinez and Casadevall 2006). C. albicans biofilms are

extremely resistant to azoles (d'Enfert 2006). There are several mechanisms that contribute to the

resistance of C. albicans biofilms, including increased levels of β-(1,3)-glucan (Nett, Lincoln et

al. 2007), but the most important may be the advent of persister cells. Biofilms offer refuge from

antifungal drugs and some host immune response, which facilitates the development of persister

cells that are able to tolerate high drug concentrations. Persisters are a phenotypic variant that is

only able to arise from biofilms (LaFleur, Kumamoto et al. 2006). Persister cells are frequently

found in bacterial biofilms; while bacterial persisters are quiescent, it is unclear whether fungal

persisters are quiescent as well (LaFleur, Kumamoto et al. 2006). Persisters are thought to be a

major factor affecting the recalcitrance of fungal infection to treatments.

26

1.6 Strategies for studying the evolution of drug resistance

1.6.1 Examining clinical isolates

One of the best ways to study how resistance to antifungals evolves in the human host is to

examine fungal specimens that have been isolated from an infected individual over time. The

most clinically relevant mechanisms of resistance can be elucidated and ultimately targeted to

abrogate resistance. However, exclusively examining clinical isolates can be limiting due to the

small sample sizes and the inability to control population parameters such as the number of

generations, effective population size and the genotype of the initial, susceptible strain. This

makes it challenging to determine what selective pressures directly contribute to the evolution of

resistance. For these reasons, in vivo evolution of antifungal resistance studies are complemented

by in vitro experimental evolution counterparts (Figure 1.2), as discussed in a later section. This

section focuses on studies of the evolution of drug resistance in the human host.

27

Figure 1.2. Studying the evolution of resistance to antifungals. The evolution of resistance to

antifungals can be monitored in real time and the mechanisms of resistance can be dissected, in

both in vitro and in vivo evolved strains. A) Propagating a strain in the presence of antifungal

selects for cells that have acquired a mutation that permits growth in the presence of the drug

(grey cells). With continued propagation, additional mutations can accumulate (black cells) that

confer resistance, abrogate the cost of resistance or have no beneficial effect on their own

(‘hitchhiking’ mutations). B) Resistance evolves over time in the human host undergoing

28

antifungal treatment. Serial isolates are taken from the host and their resistance to the

administered antifungal can be assayed. Frequently, multiple mutations conferring resistance are

found in clinical isolates (grey and black cells). The image of the human form was generously

provided by Carolyn Thomas. C) The clonality of evolved strains must be confirmed in order to

determine how frequently beneficial mutations arose. Clinical isolates can represent several

strains that the host was infected with. D) Resistance mechanisms can be determined in evolved

strains by several methods.

29

1.6.1.1 Population dynamics of fungi in the human host

When an antifungal-resistant fungal strain arises in an infected patient, it can be due to resistance

mutations occurring in the initial strain, or due to replacement with a resistant strain or species

(reviewed in (White, Marr et al. 1998)). Replacement with a resistant species can occur due to

intrinsic differences in drug susceptibility between related species, and due to the fact that many

fungi are environmentally ubiquitous. For example, it is well documented that during treatment

a patient with an initially azole-susceptible C. albicans strain may develop a resistant infection

due to acquisition of a species that is intrinsically less susceptible to azoles, such as C. glabrata.

It is also possible that a patient can acquire a resistant strain of the same species, and multiple

studies have focused on strain replacement in the clinical setting; between 20-33% of cases of

resistance that developed during treatment were due to strain replacement. To distinguish clonal

relationships from strain replacement requires the susceptible and resistant isolates from the

patient and involves typing methods such as restriction-length fragment polymorphism (RFLP)

analysis or multi-locus sequence typing (MLST), which both take advantage of genotypic

variability between strains of the same species. Clonal relationships among isolates would

suggest that resistance emerged in the lineage due to the acquisition of resistance mutations.

1.6.1.2 Progressive drug resistance

Matched sets of clinical isolates from fungal infections have informed the field a great deal as to

how resistance mutations arise during the course of antifungal treatment. One of the best-

characterized sets of isolates illustrates the concept of progressive drug resistance, or resistance

that increases over time as sequential isolates accumulate multiple resistance mutations (White,

Pfaller et al. 1997). This set of 17 isolates of C. albicans was collected over two years from an

HIV-infected patient who was receiving azole treatment for recurrent oropharyngeal candidiasis.

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The initial isolate in the series was highly susceptible to fluconazole treatment, but by the end of

the two-year period had acquired a level of resistance approximately 200-fold higher than that of

the original isolate. This set of isolates was extensively characterized to identify the molecular

mechanisms of azole resistance (reviewed in (White, Marr et al. 1998; Anderson 2005)).

Initially, there was a selection of a strain variant, as detected by single nucleotide

polymorphisms. This was followed by overexpression of the efflux pump gene MDR1,

mutations in the drug target ERG11, the A643V mutation in the transcriptional regulator UPC2

that resulted in overexpression of ERG11, and ultimately overexpression of the drug efflux pump

genes CDR1 and CDR2 due to mutations in the transcription factor TAC1 (White 1997; White

1997; Marr, Lyons et al. 1998; Hoot, Smith et al. 2011). The progressive accumulation of

resistance mutations in these isolates exemplifies how resistance often develops in a stepwise

fashion, with high-level resistance due to the combination of multiple mechanisms.

1.6.1.3 Whole genome sequencing to identify mechanisms of resistance

Recent advances in sequencing technology allow for whole transcriptome or whole genome

sequencing approaches to complement studies of antifungal drug resistance. For example, it

would be feasible to perform whole genome sequencing (DNA-seq) to identify acquired

molecular mechanisms of drug resistance in clinical isolates, as well as identify novel resistance

mechanisms if matched sets of resistant and susceptible isolates are available. This approach is

contingent on matched sets, because of tremendous variation in genotypes among strains that are

not clonal. Indeed, even amongst clonal isolates from the same patient, there is a baseline level

of variation in genotype in the fungal population that would complicate determining functionally

relevant mutations. In addition to genome DNA-seq, RNA-seq technology could enable the

identification of genes that are specifically overexpressed in drug-resistant isolates and thereby

illuminate mechanisms of resistance. The most reproducible setting for genome-scale analyses

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would be in vitro experimental evolution of drug resistance in the laboratory, where the initial

population and selection conditions can be carefully controlled and reproduced.

1.6.1.4 Fitness effects of resistance mutations

Genetic alterations that confer resistance to an antifungal, such as point mutations in the drug

target or specific aneuploidies, confer a selective advantage in the presence of the antifungal.

However, these mutations may cause a fitness defect in the absence of drug. For example, some

of the mutations that confer azole resistance occur in transcriptional regulators and result in

altered expression of multiple genes (e.g. UPC2, TAC1, and MRR1 mutations). The pleiotropic

effects of drug resistance may therefore be costly as discussed in the section below.

1.6.2 Using experimental evolution

A powerful method that is gaining prominence in the study of antifungal resistance is

experimental evolution. Experimental evolution generally refers to a population initiated from a

single progenitor that is propagated for several generations, such that new traits can evolve and

be monitored in real-time (Elena and Lenski 2003). This broadly appealing approach is used to

model theoretical evolutionary questions as well more pragmatic issues in strain development

(Figure 1.2).

This section will describe the contribution experimental evolution has made to our understanding

of how antifungal resistance occurs. Comparisons to more exhaustive studies in bacteria and the

model yeast S. cerevisiae will also be discussed.

1.6.2.1 Benefits and limitations of experimental evolution

In vitro evolution experiments can provide a simple model for how drug resistance is generated

in the host. The researcher can manipulate parameters and thus more explicitly determine the

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factors that give rise to drug resistance. Another benefit is that these experiments are easily

replicated so the sample size can be much greater than what can be expected from retrieving

clinical isolates from patients. Experimental evolution can be performed with strains where the

genome is sequenced, such that mutations conferring resistance can be more readily identified.

However, experimental evolution cannot capture the complexity of growth in the human host. In

the human body, organisms experience diverse challenges including variation in

microenvironments, nutrient limitation, spatial structure and competition with other, unrelated

pathogens. Despite these limitations, there has been much success in the in vitro evolution of

lineages that exhibit mechanisms of resistance found in clinical isolates (Cowen, Sanglard et al.

2000; Scully and Bidochka 2005; MacLean, Hall et al. 2010).

1.6.2.2 Experimental evolution methodology

Employing experimental evolution to study the evolution of drug resistance in fungi involves

propagating cells in the presence of an antifungal, which provides the selective pressure for the

evolution of resistance. Typically, cells are passaged by serial dilution of stationary phase culture

to fresh medium containing a concentration of antifungal that typically is inhibitory but not lethal

(Dunham 2010). It is crucial that the population size at each transfer is great enough that any

beneficial mutations (conferring resistance) that have occurred are not lost to random drift (Elena

and Lenski 2003). This process is repeated until a sufficient number of generations have occurred

for substantial changes to accrue in the population, conferring resistance. Occasionally,

propagation occurs on solid medium containing antifungal. In this instance, cells are scraped or

washed off of the plate to ensure a sufficient population size, and then transferred to a new plate.

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1.6.2.3 Experimental evolution studies in fungi

There are three major factors important in the evolution of drug resistance: the mutations

conferring resistance; the cost of maintaining resistance in terms of reduced reproduction (fitness

cost); and the nature of mutations that can mitigate this cost of resistance (compensatory

mutations). These parameters have important treatment implications: the deployment of

antifungals selects for resistance, if resistance is costly then discontinuing treatment may allow

susceptible cells to out-compete their resistant counterparts, but if the cost of resistance is

reduced by compensatory mutations, the resistant population will not be eliminated by selection.

1.6.2.4 Experimental evolution studies in C. albicans

The vast majority of experimental evolution studies with fungal pathogens have been performed

with C. albicans. C. albicans replicate populations propagated for 330 generations in the

presence of fluconazole evolved resistance to fluconazole, as well as cross-resistance to

ketoconazole and itraconazole (Cowen, Sanglard et al. 2000). The expression levels of four

genes known to be important in azole resistance in clinical isolates (ERG11, CDR1, CDR2 and

MDR1) varied among the populations, indicating the occurrence of different mechanisms of

resistance. Subsequent studies monitoring the expression of 5000 open reading frames in a subset

of these evolved lineages identified three different expression profiles that matched expression

patterns found in clinical isolates (Cowen, Nantel et al. 2002), further underscoring the utility of

using in vitro evolution as a model for in vivo evolution of drug resistance. Aneuploidy also

arose frequently in these populations and conferred resistance by increased gene dosage

(Selmecki, Forche et al. 2006). For example, an isochromosome formed by the duplication of the

left arm of chromosome 5 increased resistance through elevated expression of two genes:

ERG11, encoding the drug target, and TAC1, encoding a transcription factor that regulates

expression of the ABC transporter genes CDR1 and CDR2 (Selmecki, Gerami-Nejad et al. 2008).

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Studies examining the fitness effects of resistance mutations in human pathogenic fungi have

been performed exclusively in C. albicans to date. Fitness was measured by competing evolved

strains against their progenitor in both selective (with antifungal) and non-selective conditions,

and by measuring doubling times. Despite a predicted cost of resistance, the fitness of drug-

resistant populations in non-selective medium was just as often significantly better than the

progenitor as it was worse (Cowen, Kohn et al. 2001). In some populations, the chromosome 5

isochromosome provided a fitness advantage in both the presence and absence of fluconazole

(Selmecki, Dulmage et al. 2009). This suggests that resistance need not be costly, and if it is,

compensatory mutations occur readily enough to ameliorate this cost. Furthermore, any cost of

resistance in these lineages was abrogated with additional evolution, indicating compensatory

mutati