Multiple antibiotics in combination against extreme drug resistant acinetobacter baumannii in an in vitro pharmacokinetic pharmacodynamic model

In-vitro antibiotic synergy in extensively drug-resistant Acinetobacter baumannii: the effect of testing by time-kill, checkerboard, and Etest methods.. baumannii isolates 392.4 Synerg

MULTIPLE ANTIBIOTICS IN COMBINATION AGAINST EXTREME DRUG RESISTANT

ACINETOBACTER BAUMANNII IN AN IN-VITRO

PHARMACOKINETIC/PHARMACODYNAMIC

MODEL

LIM TZE PENG

BSc (Pharm) (Hons), NUS

A THESIS SUBMITTED FOR THE DEGREE OF DOCTOR OF PHILOSOPHY

DEPARTMENT OF MEDICINE

YONG LOO LIN SCHOOL OF MEDICINE

NATIONAL UNIVERSITY OF SINGAPORE

2013

DECLARATION

I HEREBY DECLARE THAT THE THESIS IS MY ORIGINAL WORK AND IT HAS BEEN WRITTEN BY ME IN ITS ENTIRETY I HAVE DULY ACKNOWLEDGED ALL THE SOURCES OF INFORMATION

WHICH HAVE BEEN USED IN THE THESIS

THIS THESIS HAS ALSO NOT BEEN SUBMITTED FOR ANY DEGREE

IN ANY UNIVERSITY PREVIOUSLY

_

Lim Tze Peng

21 Nov 2013

Acknowledgement

The dissertation presented before you is a piece of work that would not have

been possible without the people who accompanied and supported me in these

five rewarding years It is my utmost pleasure that I can express my gratitude

to them at the beginning of this thesis, a work that is completed with their

contributions

First, I would like to express special thanks to my supervisor, Assistant

Professor Li Yang HSU, for being the best mentor I have ever met and heard

His relentless guidance and support has made this project as perfect as it can

be By establishing the contacts between me and the right people, his

directions certainly brought this work to another level

Another important person I would like to thank is my co-supervisor, Prof OH

Min Sen, Vernon for giving me a chance to work with this wonderful project I

sincerely appreciate his support for my work

Thirdly, I am very grateful to Dr Andrea KWA Apart from being a mentor,

she is also a friend who walked by my side even in the most difficult moments

of this project She constantly reminded me of my strengths and weaknesses,

making me not only a better researcher, but a better person

I am grateful to A/Prof Vincent H TAM and his team members, including

Kimberly R LEDESMA and Dr Kai Tai CHANG, for the initial laboratory

training and critical research analytical skills as well as their guidance and

assistance in hollow-fibre infection model studies

I am grateful to A/Prof Eric CHAN and his team members, especially Ms Lee

Sun NEW, for the teaching, analysis and execution of the LC/MS/MS method

studies; this project would not be complete without them

I would like to thank A/Prof Mary NG for setting up the electron microscopy

data Her efforts in explaining and analysing results marked the first step in

understanding the resistant bacteria data

I also thank Ms Pei Yun HON for spending many hours working on the

clonality of the bacteria and preparing them for electron microscopy work Her

experience and assistance are invaluable to this project

I am also grateful to all of the co-workers of the Pharmacy research laboratory,

in particular Ms Winnie Lee and Ms Sasikala D/O Suranthran Their help and

support certainly made my studies more productive and enjoyable

I thank Jocelyn TEO and Yiying CAI for their meticulous corrections and

sincerity in proof-reading my thesis

I also would like to thank the Department of Medicine, Yong Loo Lin School

of Medicine, National University of Singapore, for giving me the opportunity

for this study

Finally, I am sincerely grateful to my family, friends and especially my wife,

Cassandra CHANG for their understanding as well as endless support and

encouragement in my life

Thank you

Formal communications arising from this thesis

Publications

Lim TP, Tan TY, Lee W, Sasikala S, Tan TT, Hsu LY, Kwa AL In-vitro

activity of various combinations of antimicrobials against

carbapenem-resistant Acinetobacter species in Singapore J Antibiot (Tokyo) 2009

Dec;62(12):675-9 doi: 10.1038/ja.2009.99 Epub 2009 Oct 30 PubMed PMID: 19876075

Tan TY, Lim TP, Lee WH, Sasikala S, Hsu LY, Kwa AL In-vitro antibiotic

synergy in extensively drug-resistant Acinetobacter baumannii: the effect of testing by time-kill, checkerboard, and Etest methods Antimicrob Agents Chemother 2011 Jan;55(1):436-8 doi: 10.1128/AAC.00850-10 Epub 2010 Oct 18 PubMed PMID: 20956606; PubMed Central PMCID: PMC3019682

Lim TP, Tan TY, Lee W, Sasikala S, Tan TT, Hsu LY, Kwa AL In-vitro

activity of polymyxin B, rifampicin, tigecycline alone and in combination against carbapenem-resistant Acinetobacter baumannii in Singapore PLoS One 2011 Apr 21;6(4):e18485 doi: 10.1371/journal.pone.0018485 PubMed PMID: 21533030; PubMed Central PMCID: PMC3080872

New LS, Lim TP, Oh JW, Cheah GJ, Kwa AL, Chan EC Optimizing

hollow-fibre-based pharmacokinetic assay via chemical stability study to account for inaccurate simulated drug clearance of rifampicin Anal Bioanal Chem 2013 Feb;405(4):1407-15 doi: 10.1007/s00216-012-6549-7 Epub 2012 Nov 24 PubMed PMID: 23180085

Conferences abstracts

Lim TP et al (Apr 2010) “Evaluation of antibiotic synergy against

multidrug-resistant Acinetobacter baumannii: comparison of three methods"20th European Conference on Microbiology and Infectious Diseases Vienna, Austria

Lim TP et al (Sep 2010) “In-vitro pharmacokinetic profiling of polymyxin B and

rifampicin using ultra-performance liquid chromatography tandem mass

spectrometry” 1st SingHealth-Duke NUS Scientific Congress Singapore

Lim TP et al (Sep 2010) “The stability of polymyxin B (PB) components &

rifampicin (R) in Muller-Hinton Broth” 1st SingHealth-Duke NUS Scientific Congress Singapore

Oral presentations

Lim TP et al (May 2010) “In-vitro activity of antimicrobials in combination

against clinical strains of extreme drug-resistant Acinetobacter baumannii to all

antibiotics including polymyxin B in Singapore” 20th European Conference on Microbiology and Infectious Diseases Vienna, Austria

Lim TP et al (May 2010) “Pharmacokinetic/pharmacodynamic modelling of

polymyxin B, rifampicin and tigecycline against pandrug-resistant Acinetobacter baumannii in an in-vitro model” 20th European Conference on Microbiology and Infectious Diseases Vienna, Austria

Awards

Best Oral Scientific Paper Presentation Singapore Pharmacy Congress 2007

Best Poster Scientific Paper Presentation Singapore Pharmacy Congress 2007 Young Investigator’s Award (Allied Health) 17th Annual Scientific Meeting

2008

Singapore General Hospital, SingHealth

Best Oral Paper Award (Allied Health) 17th Annual Scientific Meeting 2008 Singapore General Hospital, SingHealth

1.3 Acinetobacter baumannii - Mechanisms of antibiotic resistance 20

2.1 Characterisation of XDR A baumannii isolates 39

2.4 Synergy studies on the comparison of the checkerboard and Etest

2.5.2 Characterising the pharmacodynamic response in

2.6.1 Characterising the emergence of resistance during

2.6.2 In vitro time-growth studies and modelling of

2.7.6 Chemical stability study 57

2.8.1 Validating the predictive ability of the MCBT to the

CHAPTER 6 89

Pharmacokinetic validation studies on the Hollow Fibre Infection

Extending the time-kill approach and validating its predictive ability

CHAPTER 8

Multiple Combination Bactericidal Testing - Clinical applications of

Summary

Extensively drug resistant (XDR) Acinetobacter baumannii are emerging

Gram-negative bacilli associated with serious nosocomial infections The

treatment of such infections often represents a challenge to clinicians as there

are very few agents in the advanced stage of development designed to target

infections caused by such resistant organisms Combination antimicrobial

therapy is commonly used in clinical practice for the management of these

infections The present body of work aims to elucidate the most effective

combination(s) for use by clinicians for such difficult-to-treat infections The

studies presented here applied an integrated approach that utilised

susceptibility testing, time-kill studies and a novel hollow-fibre infection

model Thirty-one XDR A baumannii isolates were identified and subjected to

time-kill analysis The combination of polymyxin B plus rifampicin was able

to achieve bactericidal activity in 42% of the isolates These results were

validated in a hollow-fibre infection model under clinically relevant

pharmacokinetic antibiotic exposures This study also demonstrated the

emergence of resistance of XDR A baumannii to polymyxin B when

administered alone and TEM observations suggested the notion of extensive

outer membrane changes of the bacteria attributed to polymyxin B exposure

These two observations suggested that sub-optimal polymyxin B clinical

dosing regimens contribute considerably to the development of polymyxin B

resistance A comparison between the conventional methods (checkerboard

and Etest) of antibiotic synergy testing attempted to identify an effective way

to identify useful antimicrobial combinations to use in the clinical setting

However, there was little agreement when the two methods were compared to

the gold standard time-kill studies A novel multiple combination bactericidal

test was then explored as a decision support tool to facilitate rational

antimicrobial combination selection When compared against time-kill studies,

the new test has excellent agreement in terms of predicting inhibitory activity

of antimicrobial combinations (80-94%) In other words, it is extremely

effective at predicting antimicrobial combinations that will be doomed for

clinical failure Taken together, the results of this study demonstrated that this

approach can identify useful antibiotic combinations for clinical use

In conclusion, we have demonstrated that antimicrobial combination therapy is

a viable approach to treatment of XDR A baumannii infections The scope of

the proposed approach is wide The proposed evaluative approach is illustrated

by XDR A baumannii However, this is not confined to a specific

antimicrobial agent-pathogen combination, but is general and flexible

Consequently, the proposed method can be extrapolated to other antimicrobial

agents (e.g., antibacterials, antifungals and antivirals) with different

mechanisms of action, as well as to other pathogens (e.g., HIV and

tuberculosis) with different biological characteristics It is envisaged that we

can streamline this approach for diagnostic use in the future

List of tables

Table 1 In vitro activity of antibiotic combinations against MDR GNB

Table 2.Comparison of various methods used to assess antibiotic

Table 4 24 hour bacteria burden (log10 CFU/ml) after exposure to individual

Table 5 24 hour bacteria burden (log10 CFU/ml) after exposure to various

Table 6 Clonal group analysis of the 24 hour bacteria burden (log10 CFU/ml)

Table 7 Summary of test-values obtained by time-kill, Etest and checkerboard

Table 8 Intraday accuracy and precision (n = 3 for each concentration) 94

Table 9 Susceptibility results of A baumannii isolates, pre and post-exposure

Table 11 24 hour bacteria burden (log10 CFU/ml) for TK and MCBT after

Table 12 Agreement of MCBT to TK method based on prediction of presence

Table 13 Agreement of MCBT to TK method based on prediction of presence

List of figures

Figure 1 Simplified checkerboard testing of antimicrobial combinations

Figure 2 Cross formation placement of Etest strips for synergy testing 30

Figure 5 Schematic diagram of the in vitro HFIM adapted from Tam et al

Figure 7 Differential equations characterising the one-compartment

Figure 9 Time-kill graph of A baumannii 112 against single

Figure 10 Clonal relatedness of all A baumannii received for testing 86

Figure 11 Chromatograms of (A) blank Ca-MHB and (B) Ca-MHB

spiked with 10 µg/ml polymyxin B, 0.5 µg/ml rifampicin and

Figure 12 Stability profiles of polymyxin B at 9 µg/ml, (B) and (C)

rifampicin at 2 µg/ml and 0.4 µg/ml, respectively, in Ca-MHB at

Figure 13 Stability profiles of rifampicin at (A) 0.2 µg/ml and (B) 2

Figure 14 Typical observed pharmacokinetic profiles in the

following infection models: PB, 1 MU every 12h (A); rifampicin,

Figure 15 Microbiologic response observed in the following

infection models: polymyxin B + rifampicin, polymyxin B +

Figure 16 TEM images of parent A baumannii 8879 isolate (A-C)

Figure 17 SEM images of parent A baumannii 8879 isolate (A-B)

List of abbreviations and symbols

CHAPTER 1 Introduction

1.1 Antimicrobial resistance

Microbial resistance to antimicrobial agents is a serious problem that renders

development of new treatment options an urgent priority The alarming spread

of antimicrobial resistance is threatening our therapeutic armamentarium

(Boucher, Talbot et al 2009) It is likely that effective treatment may not be

available for many common infections in the near future and we are at risk of

going back to the pre-antibiotic era in the event of an outbreak (Landman,

Quale et al 2002) Broad-spectrum antimicrobial resistance in Gram-negative

bacteria (e.g., Acinetobacter baumannii and Pseudomonas aeruginosa) is

especially worrisome and has worldwide implications This has led to a

proposed international standardisation to describe acquired resistance profiles

in this group of organisms Multidrug-resistance is defined as

non-susceptibility to at least one agent in three or more antimicrobial categories

Extensively drug resistance (XDR) is defined as non-susceptibility to at least

one agent in all but two or fewer antimicrobial categories (i.e bacterial

isolates remain susceptible to only one or two categories of antibiotics)

Pandrug-resistance (PDR) is defined as non-susceptibility to all agents in all

antimicrobial categories (i.e no agents tested as susceptible for that organism)

(Magiorakos, Srinivasan et al 2011)

Gram-negative bacterial infections represent a major challenge in the hospital

setting Data from the US Centre for Diseases Control and Prevention showed

that gram-negative pathogens were isolated in association with 65%–80% of

all cases of intensive care unit (ICU)–acquired pneumonia, 40%–60% of all

ICU-acquired surgical-site infections, 70% of all ICU acquired urinary tract

infections, and 25%–30% of all ICU-acquired bloodstream infections

(Gaynes and Edwards 2005) Recently, the “ESKAPE” pathogens

(Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae,

Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species) were reported to be the organisms that currently cause the majority of

hospital infections and “escape” the effects of antimicrobial agents in the US

(2004, Rice 2008)

The incidence of Gram-negative antimicrobial resistance is high in Singapore

hospitals From 2006 to 2008, the incidence densities of ceftriaxone- and

ciprofloxacin-resistant Escherichia coli and imipenem-resistant Acinetobacter

spp increased significantly (Hsu, Tan et al 2010)

1.2 Acinetobacter - Taxonomy

The genus known as Acinetobacter had undergone several taxonomic changes

over the past 3 decades Currently, the genus Acinetobacter consists of

gram-negative, strictly aerobic, non-fermenting, non-fastidious, non-motile,

catalase-positive, oxidase-negative bacteria with a DNA guanine-cytosine

(G-C) content of 39% to 47% (Peleg, Seifert et al 2008) The cells are

approximately 2µm in length and they are rod-shaped during the growth phase

and become shorter and rounder resembling small cocci (spherical shape)

during stationary phase They are commonly described as cocco-bacillary in

shape, and can be found in pairs or groups

Identification of Acinetobacter to the individual species level had been fraught

with difficulties as phenotypic tests has proven to be inadequate

(Gerner-Smidt, Tjernberg et al 1991) The utilisation of molecular techniques in this

modern era through DNA-DNA hybridisation assays have shown the close

inter-relatedness of a number of clinically important Acinetobacter species

that include Acinetobacter baumannii, Acinetobacter calcoaceticus, genomic

species 3 (‘‘Acinetobacter pittii’’) and genomic species 13TU (‘‘Acinetobacter

nosocomialis’’) They are conveniently grouped together as the A calcoaceticus-A baumannii complex by clinical laboratories (Gerner-Smidt 1992) While Acinetobacter calcoaceticus is primarily a soil organism, the

remaining three of them are clinically important species Therefore, it may not

be appropriate to use this designation in a clinical context

1.3 Acinetobacter baumannii - Mechanisms of antibiotic resistance

A baumannii is increasingly XDR due to its wide repertoire of antimicrobial

resistance mechanisms and its innate ability to acquire new resistance

determinants (Bergogne-Berezin and Towner 1996, Bonomo and Szabo 2006)

As a frequently occurring pathogen associated with serious nosocomial

infections, A baumannii had been shown to be associated with unfavourable

clinical outcomes (Kuo, Lai et al 2007, Kwa, Low et al 2007) Carbapenems

are broad-spectrum antimicrobial agents that have excellent activity against a

wide variety of bacteria They have increasingly been used as first-line therapy

in institutions where there are high levels of resistance to other classes of

antimicrobial agents (aminoglycosides, fluoroquinolones and cephalosporins)

(Rahal 2008) Carbapenem resistance is now observed worldwide in A

baumannii, leading to limited therapeutic options (Peleg, Seifert et al 2008) Several mechanisms are responsible for resistance to carbapenems in A

baumannii These are reduced outer membrane permeability, penicillin

binding protein changes, and carbapenemase production (Poirel and

Nordmann 2006) Treatment of XDR A baumannii infections often represents

a challenge to clinicians and there are very few agents in an advanced stage of

development designed to target these XDR bacteria (Levin, Barone et al 1999,

Centers for Disease Control and Prevention (CDC) 2004, Maragakis and Perl

2008) This phenomenon has resulted in the revival of the polymyxins, which

are increasingly used as the last line of defence against such difficult-to-treat

infections Inevitably, growing reports of polymyxin (often the last antibiotic

class that A baumannii remain susceptible to) heteroresistance in XDR A

baumannii and even PDR A baumannii had come to light (Li, Rayner et al

2006, Hawley, Murray et al 2008) As a result, a task force from the

Infectious Diseases Society of America (IDSA) had recently identified A

baumannii as a “particularly problematic pathogen”, for which there was an

urgent need for new and effective treatment strategies (Talbot, Bradley et al

2006)

1.4 Antibiotic Combinations - Clinical rationale

Antibiotic combinations have been used for many decades for a variety of

3 Reducing potential toxicity by using lower doses than would be used in

monotherapy; and

4 Reducing the likelihood of emergence of resistant subpopulations –

this last is the rationale for the multidrug combinations used in the

treatment of tuberculosis

The focus will be on the rationale for antibiotic combination therapy in

Gram-negative bacteria (GNB) infections

1.4.1 Achievement of a synergistic effect

The most important potential benefit of combining two or more agents

together is to achieve a synergistic effect that enhances the antimicrobial

activity of any single agent alone Synergy is defined as a greater bacteria

killing effect provided by two agents combined than that provided by the sum

aminoglycosides have been extensively used in the management of serious

infections They are usually used in endocarditis, septic shock and

Pseudomonas aeruginosa infections (Leibovici, Paul et al 1997, Chow and

Yu 1999) These studies appeared to suggest that combination therapy was

associated with improved clinical outcomes especially in severely ill patients

with GNB infections However, a recent meta-analysis showed no difference

between monotherapy and combination therapy in mortality or emergence of

resistant pathogens although sub-group analysis augmented the findings of the

above earlier clinical studies (Tamma, Cosgrove et al 2012)

In summary, early clinical data suggesting the utility of combination therapy

had been used against serious infections (usually P aeruginosa) using an early

generation -lactam-aminoglycoside combination This might not relate to current therapeutic options with the availability of broad-spectrum

carbapenems and potent fluoroquinolones

1.4.2 Prevent emergence of resistance

The second rationale of using antibiotic combinations to reduce or prevent the

emergence of resistance is exemplified in the treatment of tuberculosis (TB),

acquired immune deficiency syndrome (AIDS) and malaria (Lange 1995,

Caminero, Sotgiu et al 2010, Gosling, Okell et al 2011) The success of this

approach is predicated on the rapid development of independent mechanisms

of resistance to various agents to human immunodeficiency virus (HIV) and

the selection of resistant mutant subpopulations in TB Normally, the presence

of a single drug will select out the resistant mutants that result in a “U-shaped”

regrowth phenomenon, resulting in a multiplication of bacteria population

over time Antibiotic combinations have been studied using in vitro techniques

and animal models that may help to prevent the emergence of resistance when

at least one agent is active in vitro against pyogenic bacteria (Pachon-Ibanez,

Fernandez-Cuenca et al 2006, Chait, Craney et al 2007)

1.4.3 Against highly resistant organisms

Many available drug treatments are ineffective when used alone against XDR

and PDR GNB Combination antimicrobial therapy is commonly used

clinically for the management of these difficult-to-treat infections

Combination therapy is currently our last line of defence in treating patients

infected by these highly resistant bacteria as infection control measures can

only prevent the spread of these organisms and no new effective antibiotics are

available for use currently (Durante-Mangoni, Utili et al 2014) The rationale

is that when using two or more antimicrobial agents (often with different

mechanisms of action) concurrently, an enhanced pharmacodynamic effect

may be attained It is hoped that synergistic combinations would provide an

enhanced bactericidal effect in the treatment of infections due to MDR strains

There had been numerous in vitro studies and retrospective clinical studies

that had examined combination therapy against GNB, especially the

non-fermenters (A baumannii & P aeruginosa) extensively over the past few

years Excellent reviews had been written to document the variety of antibiotic

combinations that demonstrated in vitro activity against the two opportunistic

nosocomial pathogens (Rahal 2006, Kwa, Tam et al 2008, Peleg, Seifert et al

2008) (Table 1) Antibiotic combinations that had been shown to have

enhanced activity against A baumannii when compared to that of a single

agent included polymyxin B (PB) or colistin plus rifampicin, polymyxin B

plus tigecycline, tigecycline plus rifampicin, imipenem, or azithromycin;

rifampicin plus azithromycin; sulbactam plus rifampicin, azithromycin, or a

quinolone; and the triple combination of polymyxin B, imipenem, and

rifampicin (Hogg, Barr et al 1998, Tascini, Menichetti et al 1998, Manikal,

Landman et al 2000, Yoon, Urban et al 2004, Lim, Tan et al 2009, Lim, Tan

et al 2011) (Table 1)

Table 1 In vitro activity of antibiotic combinations against MDR GNB

infections (adapted from Durante-Mangoni et al 2014)

However, clinical studies that examine clinical outcomes of combination

therapy are rare In a cohort study, 25 critically ill patients with respiratory

tract infections due to multidrug-resistant (MDR) A baumannii or P

aeruginosa were treated with intravenous and/or aerosolised polymyxin B in

combination with various antibiotics Twelve of the 25 infecting isolates were

resistant to all available antibiotics except polymyxin B Nonetheless, 79% of

treated patients survived to the end of therapy, and 41% of 22 patients

achieved microbiological clearance (Sobieszczyk, Furuya et al 2004) Patients

treated with an empirical combination antibiotic regimen directed against

Gram-negative bacteria were less likely to receive initial inappropriate

antibiotic therapy compared to monotherapy (22.2% versus 36.0%) This

suggests that combination therapy may improve clinical outcomes due to

Gram-negative bacteraemia if it is associated with more appropriate empirical

therapy

1.5 Methods for assessing drug interactions

There are a variety of techniques that are commonly used in drug combination

studies Although the ultimate aim is to reveal clinically relevant synergistic

drug interactions, the precise methods, experimental endpoints and interpretive

criteria differ widely As a result, there is no satisfactory methodology to

evaluate combination therapy and to quantify the extent of pharmacodynamic

drug interaction In addition, all these methods had not been informative in

predicting favourable clinical outcomes as they were associated with several

limitations that include but are not limited to:

• fixed drug concentrations and sampling times used

• dynamic assessment of drug interactions and number of antimicrobial combinations tested

The common methods that are relevant to clinical practice are briefly reviewed

below, along with their potential advantages and limitations (Table 2)

1.5.1 Checkerboard method

The checkerboard method (CB) is the most frequently used technique to assess

antimicrobial combinations in vitro (Elion, Singer et al 1953, Garrod and

Waterworth 1962, Sabath 1967) This test arose as a result of a modification of

an in vitro method that was devised to study interactions between anticancer

agents by exposing bacteria to varying concentrations of the anticancer drugs

(Elion, Singer et al 1953) The ease of performing this technique, simple

mathematics involved in calculating and interpreting the results are the major

factors contributing to the popularity of this method being used in studies to

evaluate synergistic combinations against bacteria The term “checkerboard”

refers to the array of tubes or microtitre wells formed by multiple dilutions of

two antimicrobial agents and the fractional inhibitory concentration (FIC)

index is the mathematical expression used to represent the interactions The

FIC is determined for each drug by dividing the minimum inhibitory

concentration (MIC) of each drug when used in combination by the MIC of

each drug when used alone The FIC index (FICI) is based on the Loewe

additivity zero-interaction theory (Berenbaum 1989) The hypothesis is based

on the fact that one drug cannot interact with itself and two drugs which do not

interact with each other should combine with each other to produce

interactions known as “synergy” or “antagonism” with FICI of <1 or >1

respectively As standard two-fold dilutions are commonly used to determine

checkerboard interactions coupled with the one-dilution fold error of single

drug susceptibility testing, the cut-offs for FICI determination were

established at <0.5 and >4 for synergy and antagonism respectively (Greco,

Bravo et al 1995, Odds 2003, Johnson, MacDougall et al 2004) (Figure 1)

Figure 1 Simplified checkerboard testing of antimicrobial combinations

The CB method has several limitations First, subjective endpoints (“cloudy”

versus “clear” wells) are employed to determine the FIC for a drug Such

assessments can only provide a “growth or no growth” response and is unable

to define dose-exposures relationships In addition, this increases the

inter-variability of the interpretation of results by different operators as well

Secondly, the underlying assumptions do not account for nonlinear

concentration-effect relationships, giving rise to unexpected results Thirdly,

the results are often examined at only one time-point, giving rise to a static

view of the drug interactions Despite these limitations, the checkerboard

technique is relatively easy to perform and remains a popular method for

assessing antimicrobial combinations

1.5.2 Epsilometer test (Etest) method

The epsilometer test (Etest) method has been used for antimicrobial

susceptibility testing since 1991(Glupczynski, Labbe et al 1991, Jorgensen,

Howell et al 1991) It is an agar diffusion method where a rectangular plastic

strip coated with a drug in an exponential gradient fashion is laid on an agar

plate spread with the test organism There is an exponential scale printed on

the other side of the strip that corresponds to the specific drug concentration

impregnated on each point of the strip After 24 hours of incubation, an

elliptical zone of inhibition is produced and the point at which the ellipse

meets the strip represents the reading of the MIC

The Etest method have been studied for synergy testing since 1993 (Hoffner

1993, Poupard 1993) The most important feature of this test is that it is very

easy to perform and can be an attractive option for clinical microbiology

laboratories when the standardised method for synergy testing is established

for routine use There are at least three modifications of this method to

evaluate antibiotic synergy One involves placing one antibiotic strip on the

agar plate for one hour and replace with the second antibiotic strip on the same

location (Poupard 1993, Bolmstrom 1995) Another way is to incorporate the

first antibiotic into the agar media itself and place the second antibiotic strip

on it (Hoffner 1993) White et al placed the two Etest strips in a cross

formation, with a 90° angle at the intersection between the MICs of the two

drugs (White, Burgess et al 1996) (Figure 2)

Figure 2 Cross formation placement of Etest strips for synergy testing

There had been numerous studies comparing and evaluating the Etest method,

checkerboard method and the time-kill method However, there was

considerable disagreement in the comparative results as each study’s

methodology was slightly different and different microorganisms were studied

(White, Burgess et al 1996, Bonapace, White et al 2000, Sopirala, Mangino

et al 2010) As with the other methods, there is no consensus on how

predictive the Etest synergy method will be with regards to clinical efficacy

However, this method is still popular as one of the in vitro methods to use as it

is significantly less time-consuming and less labour intensive as compared to

other methods

1.5.3 Time-kill studies

A different approach to the checkerboard method, time-kill studies (TKS) can

follow microbial killing and growth as a function of both time and antibiotic

combination Serial colony counts are utilised to provide a dynamic picture of

antimicrobial activity over time However, this technique is extremely tedious

and results are limited by the number of antimicrobial concentrations and/or

combinations being assessed

Interpretation of the results is conducted at the 24h time-point Bactericidal

activity is defined as ≥ 3 log10 colony-forming units per millilitres (CFU/ml) decrease in the colony count from the initial inoculum at 24 hours Synergy is

defined as a ≥ 2 log10 CFU/ml decrease in the colony count by the drug combination when compared with its most active constituent and a ≥ 2 log10

CFU/ml decrease from the initial inoculum at 24 hours while

indifference/additivity was defined as a < 2 log10 CFU/ml change at 24 hours

by the combination compared with that by the most active single agent

(National Committee for Clinical Laboratory Standards 1999) However, these

definitions assume that at least one of the drugs must be present in a

concentration which does not affect the growth curve of the test organism

when used alone (American Society for Microbiology 2011) This suggests

that at least one drug has to be used at sub-inhibitory concentrations to allow

the determination of synergism or indifference This assumption may not be

applicable when we are assessing XDR or PDR bacteria where they are

already resistant to virtually all classes of antibiotics Testing at sub-inhibitory

drug concentrations means that the antibiotic’s potential efficacy is not fully

realised This may lead to a gross under-estimate of the true synergistic

interactions between two antimicrobials and may not be clinically relevant in a

MDR or XDR infection

Using traditional methods, only fixed concentrations of drugs can be studied

However, this method can provide further insights into the overall effect of

antimicrobial interactions provided clinical relevant drug concentrations are

used and appropriate mathematical models are utilised to provide a more

detailed assessment of the pharmacokinetic-pharmacodynamic (PK-PD)

interactions of antibiotics Recently, a novel parametric method was developed

to characterise and quantify objectively the pharmacodynamic drug interaction

using TKS as the backbone The data were modelled with a three-dimensional

response surface using effect summation as the basis of null interaction The

interaction index (Ii) was defined as the ratio of the volumes under the planes

(VUP) of the observed and expected surfaces: VUPobserved/VUPexpected Synergy

and antagonism was defined as Ii values of <1 and >1, respectively.(Tam,

Schilling et al 2004) The model was extended to evaluate A baumannii It

was able to objectively rank the combined killing activities of two

antimicrobial agents when used together against a MDR A baumannii isolate

(Lim, Ledesma et al 2008)

1.5.4 In vitro pharmacodynamic models (IVPD)

A modification of the TKS would be to employ programmable pumps to

deliver antibiotics into a central reservoir culture overtime, simulating drug

concentrations achievable in man The one-compartment model was

developed to study antibiotic combinations with fluctuating drug

concentrations mimicking human pharmacokinetics (Blaser 1985) In brief, the

model consists of a central reservoir containing the organisms, a diluent

reservoir tank, and a waste reservoir tank Drugs are added to the central

reservoir to achieve peak concentrations (in humans) and the elimination

profile is simulated by the addition of drug-free diluent to the central reservoir

and removal of an equal volume of drug (and organism) containing medium

into the waste reservoir This model is robust enough to allow for the

simulation of nearly any desired elimination half-life within the limits

presented by the large volume of the central reservoir and the peristaltic

pumps used to add and remove nutrient media However, the main

disadvantage of this model is the loss of organisms during the removal of the

drug as the enumeration of viable organism is an important parameter to

determine antibiotic interactions The development of hollow-fibre reactors

eliminated all these limitations The use of these hollow-fibre infection models

allow the trapping of bacteria in the extra-capillary space (ECS) where the

ECS is defined by the space outside the fibres but within a hollow-fibres

cartridge The pore size of the fibres helps to retain the bacteria in the ECS and

allow small molecules such as drugs and nutrients to cross freely between the

fibres This system is widely used in drug studies in influenza virus,

tuberculosis and bioterrorism agents (Brown, McSharry et al 2011, Drusano,

Sgambati et al 2011, Louie, Vanscoy et al 2011) However, the system is

challenging to be applied clinically as it takes about a week for preparatory

work and significant man-hours are devoted for drug administration and

sample collection from the system

Table 2.Comparison of various methods used to assess antibiotic combinations

Many combinations can be tested

Cut-off values assume linear relationship between drug interactions

effect

Easily available commercially and fairly easy

to perform

Several modifications

of the tests available resulting in different interpretations

of endpoints

bacteriostatic effect

Drug interactions can

be evaluated over time

Labour intensive and few

combinations can be tested

at each time

bacteriostatic effect

Drug interactions can

be evaluated over time under human

pharmacokinetic conditions

Expensive and labour intensive One

or two combinations can be tested

at each time

1.6 Rationale for antibiotic combination testing

Few treatment options remain for the treatment of XDR A baumannii In view

of the lack of novel antimicrobial agents in the drug development pipeline,

antibiotic combinations that yield some in vitro activity are perhaps the best

recourse in such scenarios Due to the varied resistant genotypes that may be

exhibited by XDR A baumannii, the selection of empirical antibiotic

combination therapy may be difficult as a common effective antibiotic

combination may not work for all isolates In view of the numerous possible

combinations (e.g., from six available agents, there are 15 possible two-agent

combinations), it is difficult to compare many different combinations in a

rational manner, and antimicrobial agents combinations are often selected

empirically by clinicians under such circumstances (mostly based on prior

personal experience) This approach is poorly guided and may not be optimal

for patient care Therefore antibiotic combination testing is warranted for the

treatment of XDR A baumannii

1.7 Hypothesis

Strain-specific antibiotic combinations are effective against XDR A

baumannii isolates in Singapore

1.8 Aims

1 To elucidate efficacious antibiotic combinations against Acinetobacter

baumannii

2 To identify the common mechanisms of antibiotic resistance in A

baumannii for better understanding of the extensively drug-resistance

phenotype of the organism

CHAPTER 2 Materials and methods

2.1 Characterisation of XDR A baumannii isolates

2.1.1 Microorganism collection and selection

Clinical A baumannii isolates from the urinary tract, blood and respiratory

tract were collected from five local public sector hospitals over a three-year

period (2006-2008) by Network for Antimicrobial Resistance Surveillance

(Singapore) Genus identity was initially determined using conventional

biochemical methods and ID-GN cards (Vitek 2, bioMérieux, France) and

confirmed by a polymerase chain reaction (PCR)-based method (Chen, Siu et

al 2007) The bacteria were stored at -70°C in Protect® (Key Scientific

Products, Stamford, TX, USA) storage vials Fresh isolates were sub-cultured

twice on 5% blood agar plates (Thermo Scientific, Malaysia) for 24 h at 35°C

prior to each experiment

2.1.2 Susceptibility studies

MICs to ampicillin/sulbactam, ciprofloxacin, gentamicin, imipenem,

meropenem, aztreonam, piperacillin/tazobactam, polymyxin B, tigecycline,

ceftazidime, amikacin and cefepime were obtained by microbroth dilution

using commercial microbroth dilution panels (Trek Diagnostics, East

Grinstead, UK), performed according to the manufacturer’s

recommendations MICs to rifampicin were obtained by a modified broth

macrodilution method as described by the CLSI (Clinical and Laboratory

Standards Institute 2010)