Alexia Chauzy

Hariyanto Ih

Matthieu Jacobs

Sandrine Marchand

Nicolas Grégoire

William Couet
email: william.couet@univ-poitiers.fr.

Julien M Buyck

Pharmacodynamic

MCR-1 klebsiella pneumoniae adaptive resistance towards colistin with arn T gene overexpression. In submission

Keywords: colistin, polymyxin B, E. coli, K. pneumoniae, A. baumannii, sequential time-kill

Due to the lack of new antibiotics facing the increasing emergence of resistances, it is important to understand the mechanism and dynamics of these phenomenon.

Lipopolysaccharide (LPS) is the polymyxin main target and the most contributing component to polymyxin resistance. Plasmid-mediated colistin resistance MCR-1 (Mobile Colistin Resistance) carrying by Escherichia coli and Klebsiella pneumoniae encodes a phosphoethanolamine transferase leads to the addition of phosphoethanolamine to lipid A of LPS. However, chromosomally-encoded LPS-modifying phosphoethanolamine transferase and loss of LPS are the two primary mechanisms that have been described in colistin-resistant Acinetobacter baumannii to date. Polymyxin-resistance occurred during polymyxin treatment, but the mechanism and dynamics how these strains acquired resistance is poorly understood. Sequential time-kill (TK) were developed as an alternative approach to discriminate heterogenous subpopulations (S/R) versus adaptive resistance (AR) during colistin and polymyxin B exposure.

In this thesis we:

1. Confirm that sequential TK could discriminate between a single homogenous population of bacteria without or with adaptation (AR) and two independent subpopulations with different antibiotic susceptibilities (S/R) demonstrated by pharmacokinetics/pharmacodynamics (PK/PD) modelling.

2. Determine the molecular impact of MCR-1 in the progressive adaptation of E. coli and K. pneumoniae over chromosomal genes involved to LPS modification by using the sequential TK approach.

3. Determine the mechanisms involved in polymyxin resistance in two clinical strains of A. baumannii, isolated from a patient before and after treated with colistin.

These studies not only provide a simple approach to discriminate between two PK/PD models, but also an indication that the MCR-1 presence favor another resistance mechanism leading to high-level resistance to polymyxin. By the similar approach, we determine how colistin-susceptible and resistant A. baumannii isolates respond under polymyxin pressure, including the genes involved. Furthermore, polymyxin B showed a lower capacity to induce high-level of resistance than colistin for all bacterial species.

I would also like to extend my deepest gratitude to my co-advisor Dr Julien M BUYCK, for teaching me all about microbiology, his close supervision in biology molecular, for editing my thesis and for widening my research from various perspective. I am extremely grateful for your patience, motivation and your helpful advice. The completion of my dissertation would not have been possible without your helpful contribution.

My sincere gratitude goes to Pr Françoise VAN BAMBEKE and Pr Jean-Winoc DECOUSSER for accepting to be the evaluator my PhD thesis. I would also like to thank to Pr Titik NURYASTUTI honoring me as his presence in the jury of my thesis.

I would like to extend my sincere thanks to Pr Sandrine MARCHAND for her scientific support during my article writing, and for accepting to be president of jury of my thesis. I thank her for constant help during my study in the lab. Rigour and advice. I also had great pleasure of working with all the members of the U 1070:

To Dr Nicolas GREGOIRE, for a great support during PK/PD modeling part of my thesis.

To Dr Alexia CHAUZY, for helping me in the modeling part and answering my many stupid questions. It was a pleasure working with you.

To Dr Frederic TEWES, Dr Blandine RAMMAERT, and Dr Julien BRILLAULT for a great discussion and their precious advises.

To Eduardo, for your knowledge in PK/PD and for bearing several stupid questions regarding PK/PD To Betty, for helping me during my first year in the lab. To Rana, Grace, Shachi, and Luc for their support and maintaining a good environment in our room.

To Jennifer, Romain, Kevin, Jérémy, Théo, Emma, Bruna, Muriel, Patrice, Julian, Christophe, Agnes, Helene, Isabelle, Etienne, Vincent, and all the members of the lab, for all the fun we have had in the last few years. Their warm welcome and good humor made those four years of thesis as the most enjoyable years.

To all my friends from Indonesian student association (PPI) of French and Poitiers, for the fun and their help during my stay in French.

A very special gratitude goes out to all down at Indonesian Endowment Fund for Education (LPDP) and BUDI-LN from ministry of finance and Directorate General of Higher Education of the Republic of Indonesia, for helping and providing the funding for the study and the research. Special thanks to Pr Gérard MAUCO, who gave me the golden opportunity to do my PhD.

I am forever grateful to my parents, my sisters, and all my family member in Indonesia, for their support and their encouragement which helped me in completion of this dissertation. 2. Déterminé l'impact de la présence du plasmide MCR-1 sur les mécanismes de résistance chromosomique impliqués dans la résistance adaptative de E. coli and K. pneumoniae aux polymyxines. Hariyanto Ih, Nicolas Grégoire, William Couet

LIST OF TABLES

CHAPTER 1 GENERAL INTRODUCTION

EMERGENCE OF POLYMYXIN RESISTANCE IN GRAM-NEGATIVE BACTERIA

Antibiotic resistance has become a major threat to public health today, both in world-wide and Europe region, and has been classified as one of the three greatest threat for human health (1). Throughout European countries, the prevalence of antibiotic resistance widely increases (2). Based on the data presented by European Antimicrobial Resistance Surveillance Network (EARS-Net), 33 000 deaths each year in Europe are caused by resistant pathogens, mostly Gram-negative bacteria (GNB) (3). Infections caused by Gramnegative bacteria are recognized to be the most difficult infections to treat because of their ability to develop additional resistance mechanisms over the intrinsic drug resistance (4).

Combine resistance to several antibiotics continues to increase in some Gram-Negative bacteria (Escherichia coli, Pseudomonas aeruginosa, Acinetobacter baumannii, and Klebsiella pneumoniae), consequently reducing the available treatment options (5). The EU members collaborated to assess the situation related to this emerging multidrug resistance Gram-negative bacteria (MDR (-)) by adopted a new European One Health Action Plan against antimicrobial resistance (AMR), such as implementing national measures for the prudent use of antimicrobials, promoting collaborative research using EU funding and shaping the global agenda on AMR. (2).

A list of priority pathogens identified by World Health Organization (WHO) revealed carbapenem-resistant Gram-negative A. baumannii and Enterobacteriaceae, mainly E. coli and K. pneumoniae, as a first priority in urgent need for new treatment since the effective therapeutic options are rapidly lose their efficacy against life-threatening infections cause by these pathogens (6). Multidrug resistance in E. coli has become the major concern whereas this bacteria may cause diverse and serious disease, such as urinary tract infections and bacteremia, and acquired resistant to many antibiotics, including β-lactam, carbapenems, aminoglycosides, and fluoroquinolones by accumulating specific resistance genes (7). Another major pathogen, K. pneumoniae which may cause serious hospitalacquired infections, such as bacteremia, urinary tract infections and pneumonia, is a first carbapenem-resistant was reported in Enterobacteriaceae and exhibits a resistance rate more than 50% in European countries to all broad spectrum of antimicrobial agents including beta-lactam, fluoroquinolones, third-generation cephalosporins and aminoglycosides (8). A. baumannii strains, an opportunistic pathogen associated bacteremia, pneumonia, meningitis and urinary tract infections, were reported resistant to multiple classes of antibiotics, including β-lactam, fluoroquinolones, tetracyclines, and aminoglycosides and has reached more than 70% in both OECD and non-OECD countries (9,10). Worryingly, developing new antibiotics is less attractive for many large pharmaceutical companies. And most of the latest antibiotic found in the last 30 years like teixobactin, a peptide-like secondary metabolite, does not act against GNB (11). Thus, colistin and polymyxin B, polypeptide antibiotics belonging to the class of polymyxins, are reconsidered and expected to be the last resort to overcome these infections of multidrug resistant GNB (12,13).

Colistin (also known as polymyxin E) and polymyxin B have a narrow antibacterial spectrum, mainly against common Gram-negative bacteria in which the bactericidal activity is mediated by their electrostatic-based interaction with the Lipid A component of lipopolysaccharides (LPS) (12). Since the early 2000s, polymyxins widely attracted clinical and research interest to ensure their optimum dosing and safety for the clinical uses due to their narrow therapeutic window (14). However, being increasingly used as a last-line clinical therapeutic option, the resistance rate of E. coli, K. pneumoniae, and A. baumannii to polymyxins has been pushed (7,15). Lipopolysaccharides modification by the addition of 4-amino-4-deoxy-L-arabinose (L-Ara4N) and phosphoethanolamine (PEtN) in the lipid A is the most common resistance mechanisms developed by polymyxin-resistant Enterobacteriaceae, mainly E. coli and K. pneumoniae that decrease the net charge of lipid A leading to decreased polymyxin affinity (16). Two-component systems (TCSs) involving

PmrA/PmrB and PhoP/PhoQ have a role in these mechanisms wherein their activation is triggered by environmental stimuli and specific mutations, and subsequently, result in the alteration of LPS-modifying genes expression (17). Different from Enterobacteriaceae, nonfermentative bacilli A. baumannii provide two primary mechanisms in polymyxin resistance, including LPS modification by the alteration of lipid A and the complete loss of LPS as a result of inactivation of lipid A biosynthesis genes, lpxA, lpxC, and lpxD, lead to polymyxin resistance (18,19).

For several years, polymyxin resistance has been known by the involving of chromosomal mutations but in 2015, Plasmid-mediated colistin resistance MCR-1 was firstly reported in China (20). Since strains containing MCR-1 isolated from human and animal have been detected all over the world (21). It was reported in E. coli study that mcr-1 gene not only mediated polymyxins resistance by encoded the expression of PEtN in lipid A, as its primary mechanism, but also disturb the biosynthesis and transport of efflux pump lipoprotein which involved in polymyxin resistance (22). However, molecular impact of MCR-1 presence to lipopolysaccharide modification genes regulated by two-component systems is poorly described.

CHAPTER 2

LITERATURE REVIEW

LITERATURE REVIEW Polymyxins: The arising of "old" class antibiotics

I. POLYMYXINS: The Arising of "Old" Class Antibiotics

Polymyxins was approved for clinical use in the late 1950s and it is one of the primary classes of antibiotics with activity against most Gram-negative bacteria. The clinical use of colistin and polymyxin B was limited in 1970s due to their serious toxicity after parenteral administration, including nephrotoxicity and neurotoxicity. Between 1980s and 1990s its parenteral use was almost completely discontinued and they were then replaced by novel, more active and less toxic antimicrobial agent, such as aminoglycosides, quinolones and β-lactams (12,13,23). However, the increasing multidrug-resistant (MDR) Gram-negative pathogens together with the decrease of new antimicrobial agents in this last two decades has forced physician to reintroduce polymyxins antibiotics as a last-line therapeutic option against life-threatening infection (24,25). As a consequence, since mid-1990s, colistin and polymyxin B are used as the last resort for the treatment of infections caused by carbapenem-resistant Enterobacteriaceae, Acinetobacter baumannii, and Pseudomonas aeruginosa that are resistant to all aminoglycosides, quinolones and β-lactams (14,17).

However, over the last 15 years, research and clinical interest to colistin and polymyxin B have increased and have attracted government and other public grant bodies to establish its preclinical and clinical research due to the increase of its use in clinical practice. Thus, to harmonize the information about its use, first international conference on polymyxins in Prato, Italy, in 2013 resulting 'Prato Polymyxin Consensus' was held, and subsequently maintained each year (26). Moreover, the international consensus guidelines for the optimal use of the polymyxins is finally available and published in 2019 showing a serious effort to optimize the clinical use of polymyxins (27).

DISCOVERY OF THE FAMILY "POLYMYXIN"

The polymyxins is a cyclic lipopeptide antibiotic that was originally isolated in 1947 from the soil bacterium Paenibacillus polymyxa subsp. Colistinus (previously known as Bacillus polymyxa) concurrently by three different research group (28)(29)(30). First published in United

States of America by Benedict and Langlykee in July 1947 and then in the same month by Stansly et al., they were describing a secondary metabolite compound isolated and purified from Paenibacillus polymyxa, an antimicrobial substance which they named as "Polymyxin". They found that this compound on agar could inhibited the growth zone of Salmonella schottmuelleri that often cause paratyphoid fever in poor and rural communities across North America during 1930s. One month later in 1947, Ainsworth and co-workers from England had published their research about the identification of an antibiotic compound from the soil organism identified as Bacillus aerosporus that they called as "Aerosporin". "Polymyxin" and "Aerosporin" had selective antibacterial activity with activity against Gram-negative bacteria, and furthermore, later publication in a year after had identified that these two compounds showing the similar basic peptide (31). Subsequently, further research to identify the pharmacological properties and microbial activity of both compounds had described that the antibiotic called "Aerosporin" and "Polymyxin" had a similar antibacterial spectrum and biological activity. It was concluded that these two antibiotics belonged to the same class of antimicrobial compounds (32,33).

A consensus had reached by an international agreement that for all antibiotics derived from Paenibacillus polymyxa was named as Polymyxin (34). Consequently, "Aerosporin" was renamed as polymyxin A and "Polymyxin" was renamed as polymyxin D. Moreover, during this period other polymyxins isolated from same Paenibacillus polymyxa were characterized as polymyxin B, polymyxin C, and polymyxin E (also known as Colistin) (35). Although each polymyxin group has similar chemical structures and show similar antimicrobial activity, they exhibited striking differences in their cell toxicity. It was performed that polymyxin A, C and D showed severe reversible nephrotoxicity, while polymyxin B and polymyxin E (colistin) were less toxic after in vivo examination in dog and rabbit (36).

Generally, the polymyxin toxicity is associated by their N-terminal faty acyl segment (37). Further studies were performed then several reports had explained indicating the less renal injury were shown by colistin and polymyxin B among five polymyxins groups, and likely, this is a reason of only colistin and polymyxin B were available and preferably adopted in clinical practice until present (36,38).

COLISTIN AND POLYMYXIN B

All polymyxins from each group were generelized by their similar pentacationic polypeptides structures like ilustrated in Table 1, which are consisting of a cyclic heptapeptide amidelinked loop between the amino group of the side chain of diaminobutyric acid (Dab)

residue at position 4 and carboxyl group of the C-terminal threonine residue, a linear tripeptide and a fatty acid tail linked to normal N-terminal of the tripeptide (14). Polymyxin B is generally defined by the presence of D-phenylalanine residue at position 6, L-leucine residue at position 7 and L-Dab residue at position 3 (Table 1). To date, seven individual polymyxin B components have been identified with polymyxin B1 and polymyxin B2 are always the major lipopeptide components with two minor components form the same "group" in its commercial formulations and the total of these major components content should be not less than 80% [START_REF] Matthaiou | Risk factors associated with the isolation of colistin-resistant Gram-negative bacteria: A matched case-control study[END_REF](40)(41).

Interestingly with colistin, when it was firstly described, colistin was considered as a different entity from polymyxin antibiotics (42), until further chemical investigating determined that it has very similar structure with polymyxin E and it was concluded that they were a same compound (43). (44). It must constitute ≥77% of the total content of colistin A and colistin B together with three other minor components according to the British (BP) and European Pharmacopeias (Ph. Eur.).

Either colistin or polymyxin B are natural products prepared by fermentation, so the proportion from each component can vary from each brand and even among the batches from the same manufacturer. The commercial formulations differ between polymyxin B and colistin will be discussed in detail in "clinical use" part, include their impacts on in vivo disposition.

Overall, polymyxins are molecules that contain rich of hydrophobic part and hydrophilic parts make them as amphipathic compounds.

• Hydrophobic and hydrophilic domains were separated by exo-cyclic linear tripeptide sequence and cyclic ring heptapeptide giving these molecules as amphipathic structure that important for its antimicrobial activity.

• Dab residues (NH2) carrying positive charged of polymyxin as hydrophilic part of polymyxin will bind to negative charged phosphate group of lipid A outer membrane and the hydrophobic part of polymyxins, N-terminal fatty acyl group and hydrophobic residues (position 6 or 7), will make an hydrophobic contacts with fatty-acyl chains of lipid A.

• These interactions will destabilized the Gram-negative bacteria outer membrane leading to the lysis of bacteria cells (45). Furthermore, this mechanism will be further detailed in the part of 'mechanism of action'.

• Not only accounted for its antimicrobial activity, but also the hydrophobic properties of the N-terminal fatty acyl group are presumably as the source of the nephrotoxicity of polymyxin (13,[START_REF] Gallardo-Godoy | Activity and Predicted Nephrotoxicity of Synthetic Antibiotics Based on Polymyxin B[END_REF].

MECHANISMS OF ACTION AND ANTIBACTERIAL SPECTRUM

LIPOPOLYSACCHARIDE STRUCTURE OF GRAM-NEGATIVE BACTERIA

Different from Gram-positive bacteria, the cell envelope of Gram-negative bacteria (GNB) consists of the inner membrane, peptidoglycan, and are surrounded by an additional membrane, named outer membrane (OM) (Fig. 1). The outer membrane of Gram-negative bacteria play an important role to protect them from the external substances, including antimicrobial agents, whereas polyanionic lipopolysaccharide (LPS) of the outer membrane has an important role to regulate the compounds permeability [START_REF] Khadka | Lipopolysaccharide-Dependent Membrane Permeation and Lipid Clustering Caused by Cyclic Lipopeptide Colistin[END_REF]. The

LITERATURE REVIEW Polymyxins: The arising of "old" class antibiotics

Lipopolysaccharide, the major compound in the outer membrane are important for the bacteria survival where their detailed structure could differ from one bacterial species to another and even could be different in the same bacterial species, which is given by their genetic information, but consistent for their basic structure [START_REF] Wang | Lipopolysaccharide: Biosynthetic pathway and structure modification[END_REF]. O-antigen repeats (O polysaccharide) are displayed on the surface of bacterial cells that made of a chain from several types of repeating sugar and act as hydrophilic polysaccharide [START_REF] Ebbensgaard | The Role of Outer Membrane Proteins and Lipopolysaccharides for the Sensitivity of Escherichia coli to Antimicrobial Peptides[END_REF][START_REF] Wang | Lipopolysaccharide: Biosynthetic pathway and structure modification[END_REF]. Second

LITERATURE REVIEW Polymyxins:

The arising of "old" class antibiotics

POLYMYXINS: Mode of Action

Lipid A has a key role in polymyxins antimicrobial action by their charged-based interaction.

Dab residues (NH2) carrying positive charged as hydrophilic part of polymyxin will bind to negative charged phosphate group of lipid A outer membrane, while the hydrophobic part of polymyxins, N-terminal fatty-acyl group and hydrophobic residues (position 6 / 7) will make a hydrophobic contact with fatty-acyl chains of lipid A. These electrostatic and hydrophobic binding combination will produce a strong interaction between polymyxin molecule and LPS by forming an envelope-like fold conformation (45). Furthermore, the positive charge of polymyxin will displace the membrane-stabilizing magnesium (Mg 2+ ) and calcium (Ca 2+ ) ions, which are important as a stabilizer for the outer membrane by bridging the adjacent lipid A molecules. Displacing of these divalent cations will have an impact on destabilization of the outer membrane, increase cell permeability, leakage of cell-contents, lysis cell, and finally, bacterial cell death (45,[START_REF] Dhariwal | Colistin: Re-emergence of the "forgotten" antimicrobial agent[END_REF][START_REF] Falagas | Colistin: The Revival of Polymyxins for the Management of Multidrug-Resistant Gram-Negative Bacterial Infections[END_REF][START_REF] Trimble | Polymyxin: Alternative Mechanisms of Action and Resistance[END_REF]. Bacteria cells lysis has a consequence at risk producing amount of endotoxins causing-fever agents and it was reported that colistin has a potent action to inhibit it by neutralizing the endotoxin [START_REF] Dhariwal | Colistin: Re-emergence of the "forgotten" antimicrobial agent[END_REF].

The outer membrane is not the only target of polymyxins. As we can see in Figure 3,

secondary

ANTIBACTERIAL SPECTRUM

The structural similarities between colistin and polymyxin B are given by both compounds, many aspects, such as clinical uses, toxicity, mode of action, and antimicrobial spectrum activity are shared by both as well [START_REF] Kwa | Polymyxin B: similarities to and differences from colistin (polymyxin E)[END_REF]. For antimicrobial activity, they exhibit a narrow antibacterial spectrum, mainly against common Gram-negative bacteria. Broth microdilution method was agreed as a standard reference method with following notes (64):

• Cation-adjusted Mueller-Hinton Broth as the reference media

• No additives may be included (including polysorbate-80 or other surfactants)

• Trays must be made of plain polystyrene

B. CLINICAL PRACTICE

Colistin is widely used as intravenous formulations as CMS, an inactive prodrug, to treat infections caused by MDR and extensively drug resistant (XDR) Gram-negative pathogens (27). CMS can be administered intramuscularly although is not commonly used in clinical practice regarding to its severe pain at the injection site and its variable absorption (12).

Colistin has also been formulated for oral administration route for selective intestinal infection and is used as topical administration for bacterial skin, eye and ear infections (12).

However, colistin and its prodrug CMS are the only polymyxins approved for clinical use in the European countries based on the completes review of polymyxins-based medicine by European Medicines Agency [START_REF]European Medicines Agency completes review of polymyxin-based medicines. Recommendations issued for safe use in patients with serious infections resistant to standard antibiotics[END_REF].

Compare to polymyxin B, CMS is preferred to treat urinary tract infection, because the conversion to colistin from its prodrug mostly in the urinary tract, but as consequently has a potential risk to renal injury as well [START_REF] Li | Pharmacokinetics of colistin methanesulphonate and colistin in rats following an intravenous dose of colistin methanesulphonate[END_REF]. In addition, Intravenous CMS is indicated for the treatment of serious infections due to aerobic Gram-negative bacteria in patients with limited treatment options while inhalation of CMS is limited to chronic pulmonary infections due to P. aeruginosa with cystic fibrosis in adults with recommend dose is 1 to 2 million IU given 2 to 3 times a day and children 0.5 to 1 million IU twice daily [START_REF]European Medicines Agency completes review of polymyxin-based medicines. Recommendations issued for safe use in patients with serious infections resistant to standard antibiotics[END_REF].

A target plasma colistin Css,avg of 2 mg/L for systemic administration of CMS was recommended based on three considerations [START_REF] Nation | Dosing Guidance for Intravenous Colistin in Critically Ill Patients[END_REF]. First, it based on colistin binding in plasma which is around 50%. Second, to achieve its bactericidal activity with an MIC of 2 mg/L against an isolate on the thigh infection model. And third, both risk incidence and severity of acute kidney injury (AKI) are increased for concentration greater than 2 mg/L (27). Finally, to achieve this desired target average steady-state plasma concentration, determining the initial daily maintenance dose is required, and subsequently, monitoring creatinine clearance (Clcr) and daily dose adjustment are also required (27).

POLYMYXIN B

A. COMMERCIAL PREPARATION been defined before since it was firstly discovered. A very similar structure and antimicrobial spectrum shared by colistin and polymyxin B have made a conclusion that they have similar pharmacokinetic profile. The study always focused on CMS, the prodrug of colistin, and its result cannot be extrapolated as polymyxin B result whereas polymyxin B is administered as its active compound. Furthermore, a further study has found that polymyxin B exhibited a superior PK characteristic compare to CMS where it is reliable and rapidly achievable to maintain a desired concentration in human plasma, which is important for critically ill patients (27).

The risk of renal injury is less found in polymyxin B compare to colistin and this is a potential advantage for its clinical use over CMS [START_REF] Zavascki | Nephrotoxicity of Polymyxins: Is There Any Difference between Colistimethate and Polymyxin B?[END_REF]. No need dose adjustment of polymyxin B for the patient with renal impairment because this drug is not eliminated in the kidneys, and in addition, a clinical PK studies show that polymyxin B clearance does not depend on creatinine clearance (Clcr). Moreover, a large clinical study was started in 2016 and first result estimate publish in 2020 1 . This is a first study about PK/PD/TD profiles of IV Polymyxin B on patients with pneumonia and/or bloodstream infection.

• Overall, colistin and polymyxin B exhibit an indistinguishable in vitro PD activity with identical potencies of antibacterial spectrum against MDR and XDR Gram-negative pathogens as shown by their MICs

• In vitro and murine thigh and lung infection models have been used to elucidate the PK/PD index of colistin while the available data for polymyxin B are fewer even rare.

Free-drug area under the concentration-time curve to MIC ratio (fAUC:MIC) is the best PK/PD index to determine antibacterial activity, showing a higher tolerated systemic dose of polymyxin B is needed to obtain 1 log10 bacterial killing compare to colistin (27). The highest tolerated dose of polymyxin B to obtain 2 log10 reduction in bacterial count was not achieved whereas it can be achieved by colistin with the dose still appropriate to reach Css,avg of 2 mg/L as a target plasma of colistin (27).

• In contrast in human, polymyxin B shown an excellent PK characteristic compare to colistin, since polymyxin B is administered as its active compound with lower risk to cause nephrotoxicity although CMS is preferred to treat urinary tract infection because the conversion to colistin from its prodrug mostly in the urinary tract (27).

As a recommendation, clinicians should have access to these both parenteral products so they can choose the better option in any particular circumstances.

LITERATURE REVIEW

Gram-negative Bacteria: Emergence of MDR pathogen

II. GRAM-NEGATIVE BACTERIA: Emergence of Multidrug Resistance Pathogen

Antimicrobial resistance is the ability of a microorganism to resist the action of one or more antimicrobial agents (5). Each year, more than 670.000 infections due to bacteria with antimicrobial resistance occur in European Union countries causing 33.000 deaths and costs abouts 1.1 billion euros for the health care systems of European countries [START_REF]Antimicrobial Resistance Tackling the Burden in the European Union: OECD-ECDC Briefing Note[END_REF]. A list of priority pathogens identified by WHO revealed that carbapenem-resistant Gram-negative

Acinetobacter baumannii and Enterobacteriaceae, mainly Escherichia coli and Klebsiella pneumoniae, as a first priority in urgent need for new treatment since the effective therapeutic options are rapidly lose their efficacy against life-threatening infections cause by these pathogens (Fig. 4) (5,6).

P. aeruginosa, A. baumannii, K. pneumoniae and E. coli are the most common GNB that may cause healthcare-acquired infections and they may develop resistance to almost classes of antibiotics by multiple mechanisms (11). In this part, we focused on two Gramnegative Enterobacteriaceae, particularly E. coli and K. pneumoniae, and a nonfermentative bacillus isolate, A. baumannii.

ENTEROBACTERIACEAE

E. coli and K. pneumoniae are by far the most common Enterobacteriaceae that can cause both hospital-and community-acquired infections (3). Resistance percentages were generally higher in K. pneumoniae than in E. coli, and moreover, the emergence of carbapenems-resistant Enterobacteriaceae and Extended-spectrum-β-lactamase (ESBL)producing Enterobacteriaceae are rising over the last decade thereby classified them as the pathogen that urgent and serious to treat [START_REF] Peleg | Hospital-Acquired Infections Due to Gram-Negative Bacteria[END_REF][START_REF] Taneja | Introductory Chapter: Stepping into the Post-Antibiotic Era-Challenges and Solutions[END_REF]. In this part we detailed more about

PATHOGENIC ESCHERICHIA COLI

First identified in 1885, Escherichia coli has become one of the most bacterial species that comprehensively studied. They are easy to grow and easy to manipulate in the laboratory scale, such as genetic manipulation, and naturally acquired mobile genetic elements [START_REF] Clements | Infection strategies of enteric pathogenic Escherichia coli[END_REF][START_REF]Bacterial pathogenesis: a molecular approach3rd ed[END_REF]. Apart from their beneficial as flora normal for human and animal intestine, some E. coli strains have evolved pathogenic mechanisms and may cause the disease in human and animal as well [START_REF] Clements | Infection strategies of enteric pathogenic Escherichia coli[END_REF][START_REF]Bacterial pathogenesis: a molecular approach3rd ed[END_REF]. Habitat and genetic exchange are the primary reasons why E. coli can progress to many different forms of disease symptoms and outcome [START_REF]Bacterial pathogenesis: a molecular approach3rd ed[END_REF]. Virulence factors and secreted protease, that are differently produced from one strain to another and are crucial determinants for the progression of these bacteria to cause a wide variety of disease [START_REF] Tapader | Secreted proteases: A new insight in the pathogenesis of extraintestinal pathogenic Escherichia coli[END_REF] where the failure rate of fluoroquinolone treatments is high [START_REF] Kang | Clinical Practice Guidelines for the Antibiotic Treatment of Community-Acquired Urinary Tract Infections[END_REF][START_REF] Pitout | Extraintestinal Pathogenic Escherichia coli: A Combination of Virulence with Antibiotic Resistance[END_REF]. But since late 1990s the emergence of antibiotic resistance is on rise, the management of therapy is becoming complicated (3,[START_REF] Pitout | Extraintestinal Pathogenic Escherichia coli: A Combination of Virulence with Antibiotic Resistance[END_REF]. This species has an ability to accumulate genes encoding resistance, mostly through horizontal gene transfer. It was reported that the acquisition of genes encoding extended-spectrum β-lactamases (resistance to broad-spectrum cephalosporins), plasmid-mediated quinolone resistance (resistance to fluoroquinolone), 16S rRNA methylases (resistance to aminoglycoside) and an increasing threat is carbapenemases, which may confer resistance to carbapenems and all available β-lactam antibiotics (3,7,[START_REF] Pitout | Extraintestinal Pathogenic Escherichia coli: A Combination of Virulence with Antibiotic Resistance[END_REF]. Furthermore, the ability of Enterobacteriaceae to spread these resistance genes via cross-transfer of plasmid between inter-species and between animal and human made it worse to play a role in emergence of multidrug GNB.

KLEBSIELLA PNEUMONIAE

First described in 1882, Klebsiella pneumoniae was a species isolated from the lungs of patients who died from pneumoniae [START_REF] Martin | Colonization, Infection, and the Accessory Genome of Klebsiella pneumoniae[END_REF]. Similar with E. coli, this species is considered as commensal and opportunistic pathogen that is widely found in the mouth, skin and intestine.

K. pneumoniae is the third leading cause of hospital-acquired infection (HAIs) since it is often found in hospital setting and medical devices as well [START_REF] Li | Molecular pathogenesis of Klebsiella pneumoniae[END_REF]. Furthermore, K.

pneumoniae can be found in urinary tract, respiratory tract and blood causing UTIs, pneumoniae and bloodstream infections [START_REF] Martin | Colonization, Infection, and the Accessory Genome of Klebsiella pneumoniae[END_REF][START_REF] Li | Molecular pathogenesis of Klebsiella pneumoniae[END_REF][START_REF] Podschun | Klebsiella spp. as Nosocomial Pathogens: Epidemiology, Taxonomy, Typing Methods, and Pathogenicity Factors[END_REF]. In most case, K. pneumoniae infections occur during hospitalized or in patients with immunocompromised [START_REF] Mandell | Mandell, Douglas, and Bennett's principles and practice of infectious diseases[END_REF].

Colonization of gastrointestinal tract is an important reservoir for K. pneumoniae in healthcare-associated infections [START_REF] Gorrie | Gastrointestinal Carriage Is a Major Reservoir of Klebsiella pneumoniae Infection in Intensive Care Patients[END_REF][START_REF] Martin | Molecular Epidemiology of Colonizing and Infecting Isolates of Klebsiella pneumoniae[END_REF]. Disease-associated immunosuppression have been identified as another risk factor for community-and hospital-acquired infection of K.

pneumoniae such as cancer, diabetes mellitus and alcoholism [START_REF] Happel | Alcohol, immunosuppression, and the lung[END_REF][START_REF] Tsai | Characteristics of Klebsiella pneumoniae bacteremia in community-acquired and nosocomial infections in diabetic patients[END_REF][START_REF] Tsay | Characteristics of Bacteremia Between Community-Acquired and Nosocomial Klebsiella pneumoniae Infection: Risk Factor for Mortality and the Impact of Capsular Serotypes as a Herald for Community-Acquired Infection[END_REF]. Electrolyte and fluid disorder, neurologic disorder, and prior hospital admission have been identified as well as risk factor associated with hospital-acquired infection [START_REF] Martin | Molecular Epidemiology of Colonizing and Infecting Isolates of Klebsiella pneumoniae[END_REF].

K. pneumoniae employs several virulence factors (VFs) for survival, mostly on their surface structure, and in evading the host immune defense during infection, such as capsule polysaccharide, lipopolysaccharide, outer membrane protein (OmpA and OmpK36), and the efflux pump AcrAB [START_REF] Martin | Colonization, Infection, and the Accessory Genome of Klebsiella pneumoniae[END_REF][START_REF] Li | Molecular pathogenesis of Klebsiella pneumoniae[END_REF]. LPS variations have been found that play a role in the emergence of K. pneumoniae resistance to antimicrobial peptide such as polymyxin antibiotic that will be further detailed in the chapter 3 of "polymyxins resistance" (100). The emergence of hypervirulent K. pneumoniae (hvKp) infections are on rise at last 3 decades [START_REF] Martin | Colonization, Infection, and the Accessory Genome of Klebsiella pneumoniae[END_REF]101). hvKp is an evolving pathotype of classical K. pneumoniae (cKp) and more virulent (101). Clinicians are familiar with cKp as an opportunistic pathogen but hvKp is the best describe as a virulent pathogen.

A. EPIDEMIOLOGY OF K. PNEUMONIAE INFECTIONS

Klebsiella pneumonia is the third leading cause of hospital-acquired infections after

Clostridium difficile and Staphylococcus aureus in the United States (9.9%) and the third cause of hospital-acquired pneumonia for ICUs patients receiving ventilator after 48 hours hospitalized, still in the same country (102). This species is also the second leading cause of bloodstream infection with mortality rate around 20-30% or 1.3 per 100,000 people in US [START_REF] Podschun | Klebsiella spp. as Nosocomial Pathogens: Epidemiology, Taxonomy, Typing Methods, and Pathogenicity Factors[END_REF]102). UTI is the most common infection caused by K. pneumoniae either associated with diabetes mellitus or catheter-associated UTIs (103). K. pneumoniae was also reported to be responsible for 13% of wound/surgical site infections (102).

The prevalence of Kp infections in Western countries range from 5-35%, while in Asian countries were various from 18% to 87.7% in stool from health adults [START_REF] Gorrie | Gastrointestinal Carriage Is a Major Reservoir of Klebsiella pneumoniae Infection in Intensive Care Patients[END_REF]104).

Nasopharyngeal colonized by K. pneumoniae in healthy humans are 1-5% in western countries while in Indonesia it was found 7% in children <10 years and increase with age (15% in adults) (105). In Indonesia, K. pneumoniae was the most common bacterial agent identified and potential increase the incidence of infection (14%) (105). However, obtaining data from hvKp is quite challenging since the specific biomarkers are not always used to determine it from cKp. In Korea, hvKp colonization was found 4.6% in healthy humans (based on K1 capsule and ST23) and It was found 1.3% in Australia. hvKp colonization rates were found various in Asian countries, from 0-16.7% based on K1 and K2 capsule types which are not really specific for determination (104). However, the hvKp prevalences are being reported increasing worldwide and with this awareness, the valid biomarkers are hopefully established in the future in order to help the clinical therapy decisions leading to good therapy outcome (106). The hvKp proportion data in various geographic locales are summarized in Table 3. a Defined by the presence of iuc or rmpA or rmpA2

In France, hvKp has emerged in last decade and these infections caused multi-organ failure compare to non-hvKp infections (108, 109). A 5 years observation study in a France hospital displayed that more than half (55,9%) K. pneumoniae infections were acquired in the ICU (108). 45.5% of these acquired-infections are associated with ventilator-acquired pneumoniae and 46.1% of acquired-ICU K. pneumoniae infections were caused by hvKp (108). This study also revealed that the initial infections of hvKp and non-hvKp were mostly in lung in patients with immunodepression and type-2 diabetes characteristic, and currently, hvKp are emerging as the main pathogen with liver abscesses (108, 109).

B. ANTIMICROBIAL RESISTANCE IN K. PNEUMONIAE

To date, it is impossible for clinical microbiology laboratories to differentiate between classical Kp and hvKp isolates that cause the infections leading to the failure therapy outcome. This is important since the rapid initiation of a therapy to prevent or to minimize the subsequent spread of hvKp infection corresponding to a specific infection site, such as meningitis and endophthalmitis, is needed (101). Similar to E. coli, therapy for K. Gram-negative Bacteria: Emergence of MDR pathogen pneumoniae infections become more challenging with the plasmid-mediated antimicrobial resistance acquired by MDR or XDR classical Kp and these plasmid-mediated resistances can be acquired and integrated by hvKp strains. Many novel variations of ESBL were found in K. pneumoniae and subsequently were displayed in E. coli isolates. Broad-spectrum βlactams (except ampicillin and ticarcillin that are intrinsically not active in K. pneumoniae strains), aminoglycosides, trimethoprim-sulfamethoxazole, tetracycline, fluoroquinolones and carbapenems are commonly used to treat susceptible isolates (101). For carbapenemresistant strains, ceftazidime-avibactam, colistin and tigecycline were commonly used although these agents were active in vitro but in some cases were not effective against KPC2-producing XDR hvKp strain during a lethal ICU outbreak (110).

In European countries, more than third of K. pneumoniae isolates are resistant to at least one antibiotic (Figure 6) with the highest resistance percentage showed by third-generations cephalosporins (31.7%), then by fluoroquinolones, aminoglycosides and carbapenems at 31.6%, 22.7% and 7.5%, respectively (3). Fluoroquinolones and carbapenems resistance trend were significantly increased during 2015 until 2018. In last 2018, the resistance population over three combined antimicrobials, including fluoroquinolones, third-generation cephalosporins and aminoglycosides were reported increased in European countries at 19.6% but these did not differ significantly compared to the three years before. Similar with E. coli data, there were large inter-country variations among European countries for antimicrobial groups under regular surveillance. Higher resistance percentage generally reported from southern and eastern Europe than from northern Europe (Figure 8) with the highest percentage of carbapenems resistance were reported from these countries as well.

Similar to E. coli, antimicrobial stewardship among European countries are needed to establish and targets for the reduction of antibiotic use in human should be considered, regarding to the wide inter-country variations of the resistance population among these countries.

NON-FERMENTATIVE BACILLI : ACINETOBACTER BAUMANNII

Among Acinetobacter pathogenic species, Acinetobacter baumannii is the most successful Gram-negative pathogens responsible for 2-10% hospital-acquired infections of all Gramnegative bacteria and one of the most important opportunistic pathogens responsible for skin, bloodstream, urinary tract and other soft tissues infections (111,112). Since the first identification in 1986, A. baumannii has been described as a soil organism and were thought

to not be able to cause significant human disease, but later it has started attracting the attention during the Iraq war when US veteran and soldiers with traumatic wound have been reported showing the lethal infection caused by A. baumannii also referred as "Iraqibacter" strain [START_REF]Bacterial pathogenesis: a molecular approach3rd ed[END_REF]112,113). This Multidrug-resistant (MDR) Iraq strains has been brought along to the United States by wounded soldiers and has rapidly become an opportunist diseasecausing in Walter Reed hospital then rapidly spread to the other hospital around the country (114). It is not clear whether this Iraq strain was unusually virulent, or it just happened during the war since there is nothing known about their virulence factor during that time and other susceptible strain were presented at the same time [START_REF]Bacterial pathogenesis: a molecular approach3rd ed[END_REF]114).

As an opportunistic Gram-negative pathogen, the most interesting part of A. baumannii is their ability to persist in nosocomial environment since this ability is the initial step how they develop to opportunistic infection. Health-care environments include the routine disinfection and desiccation period are commonly routine sterilization, but A. baumannii develop several mechanisms to resist disinfection, desiccation and oxidative stress (115). Acinetobacter baumannii employs several virulence factors but relatively few have been identified compare to the other Gram-negative bacteria, such as porin, capsular polysaccharide, lipopolysaccharide, phospholipase, outer membrane vesicles (OMVs) while more studies have focused on their siderophore-mediated acquires iron acquisition systems and biofilm formations (112, 114).

EPIDEMIOLOGY OF A. BAUMANNII INFECTIONS

As one of primary cause nosocomial infection in patients hospitalized in intensive care unit (ICU), A. baumannii is responsible for almost 90% among all Acinetobacter infections that caused ventilator-associated pneumoniae, septicemia, meningitis, peritonitis, UTIs and wound infections (114, 116). Among these, hospital-acquired pneumoniae and bloodstream infections are the most common clinical manifestation of A. baumannii in ICUs. The patients with risk factors, such as in patients with lower respiratory tract infections and intravascular devices followed by immunosuppression, ventilator-associated respiratory failure, previous antibiotic therapy are particularly exposed (116-118).

Overall, epidemiology in several European countries have shown various results.

Prevalence studies in the UK and Germany shown that A. baumannii isolates are rarely found in the healthy patients but predominates in hospital infections (119). In Switzerland, around 9.2% (58 per 632 cases) of carbapenem-resistant or intermediate strains were identified from 2005-2016 whereas various results have been shown from each region but stable over the studied period (120). A study in France from December 2010 until August 2011 collected from 1,213 healthcare facilities have been identified that the most frequent infections associated carbapenems-resistant A. baumannii isolates were respiratory (34%), blood (19%), and cutaneous (19%) infections with colonization were mostly found in gastrointestinal tract (46%) and respiratory (36%) (121). Intensive care units are the hospital ward where the most cases have been found (53%) in France, followed by medical wards, chirurgical wards and burn care centers with 21%, 15% and 1.5%, respectively. The mortality rate was reported of 17.7% from the same studies periods (121).

ANTIMICROBIAL RESISTANCE IN A. BAUMANNII

The emergence of carbapenem-resistant A. baumannii are on rise with the cases rates are more than 90% all over the world and responsible for the high significantly mortality rate compares to the carbapenem-susceptible A. baumannii strains (122). In France, the carbapenem-resistant A. baumannii population is polyclonal with eleven sequence types have been identified so far. Around 82% of the total isolates harbored the BLAOXA-23 gene which is responsible for imipenem resistance (121). Polymyxins (colistin and polymyxin B), tigecycline, minocycline, sulbactam and amikacin often used as a current therapeutic option for carbapenems-resistant isolates (122). Drug combinations of these drugs have been used as well for carbapenems-resistant A. baumannii infections whereas no significant superior results either in preventing the resistance or its clinically outcome compare to monotherapy have been provided (123, 124).

From the Figure 7, the resistance to one or two antimicrobial group was less common compare to fully susceptible isolates or combined resistance to all three antimicrobial groups (fluoroquinolones, aminoglycosides and carbapenems). For the single resistance to one antimicrobial group, the highest mean resistance percentage was reported from fluoroquinolones with 36.2%, followed by aminoglycosides and carbapenems that respectively shown similar percentages to 31.9% (3). A large variation was exhibited among European countries with higher resistance were generally reported from Baltic countries and southern and eastern Europe. However, based on the rapid risk assessment of ECDC in 2016, the high-standard infection control and antimicrobial stewardship program has been improved as an effort to face the significant threat of carbapenem-resistant

Acinetobacter baumannii in all EU/EEA countries (125).

III. POLYMYXIN RESISTANCE IN GRAM-NEGATIVE

BACTERIA

The global spread of multidrug resistant (MDR) among Gram-negative bacteria has led to the resuscitation of polymyxins, including colistin and polymyxin B (17,126,127). In the last two decades, polymyxins have been limited to be used as a last resort treatment for infections, particularly by carbapenem-resistant P. aeruginosa, Acinetobacter baumannii, Klebsiella pneumoniae and Escherichia coli (12,16,128).

However, with the increased use of polymyxins, the emergence of polymyxin-resistant

Gram-negative pathogens are on rise and increasing worldwide (17,38,126). The prevalence of colistin resistance varied between regions and over time with the majority reports was less than 10% (129). China is considered as the world's highest users of colistin in agriculture, while Germany, Portugal, Italy, and Estonia have shown a higher user than other European countries (130). A global survey of polymyxin use was disseminated to relevant experts worldwide from 56 different countries (131). Around 45/56 countries (80%) had used of colistin in clinical practice while the rest had no access to colistin. Majority of respondents use colistin (64.1%) but only a few use polymyxin B (1.4%). This survey reveals that colistin is commonly used underdosage with only 21.2% of respondents administered a colistin-loading dose in their treatment, mainly in Europe and North America (131). The exposure of suboptimal dosage of colistin is a risk factor for the emergence of polymyxinresistant strains in Gram-negative bacteria (38).

Initiating therapy with loading dose was recommended to achieve a target average colistin plasma concentration at steady state (Css,avg) of 2 mg/L, where Css,avg lower than 2 mg/L may reduce the bacteria susceptibility to colistin (27,132). Polymyxin Resistance in Gram-Negative Bacteria

Although polymyxins have already been considered as highly nephrotoxic and neurotoxic the correct formulations, dose adjustment or discontinuation on adverse symptoms, avoidance of coadministration with other neurotoxic or nephrotoxic agents and good critical care, they could provide lower nephron and neural toxicities, and moreover, positive clinical outcomes (26,133). Recently, the first ever consensus recommendations for colistin and polymyxin B clinical usage were recently published to guide their optimal clinical use (27).

However, bacteria are able to adapt and employ several strategies to protect themselves from damaged caused by polymyxins. Modification of lipid A of lipopolysaccharide (LPS), efflux pump expression, reduce porin pathway and capsule formation are several mechanisms these bacteria using to respond and to resist polymyxins (16,[START_REF] Trimble | Polymyxin: Alternative Mechanisms of Action and Resistance[END_REF]. Uniquely,

A. baumannii developed resistance to polymyxin by complete loss of lipopolysaccharides as the initial binding target (18,19). Most of these mechanisms has been known chromosomally encoded until several studies reported that polymyxin resistance can be caused by horizontal gene transfer as well (20,134). Their resistance mechanisms will be described in this chapter to enhance the understanding of their regulatory mechanisms.

CHROMOSOMALLY-MEDIATED POLYMYXIN RESISTANCE 1.LIPOPOLYSACCHARIDE-LIPID A MODIFICATION

As explained in the first chapter, bactericidal activity of polymyxins is mediated by interaction from positive charged Dab residues (NH2) of polymyxin to negative charged phosphate group of lipid A component of lipopolysaccharide lead to the lysis of bacterial cells. Accordingly, modification of the lipopolysaccharide (LPS) molecules is the primary cause of polymyxin resistance in Gram-negative bacteria (16,[START_REF] Trimble | Polymyxin: Alternative Mechanisms of Action and Resistance[END_REF]135)

Lipopolysaccharide-lipid A could be extensively modified by the addition:

• 4-amino-4-deoxy-L-Arabinose (L-Ara4N)

• Phosphoethanolamine (PEtN)

• Galactosamine (GalN)

A. ADDITION OF OF 4-AMINO-4-DEOXY-L-ARABINOSE (L-Ara4N)

In some bacteria, such as K. Pneumoniae, the PhoP/PhoQ system can directly activates the arnBCADTEF operon, which is normally should be activated by PmrA first, leading to the addition of L-Ara4N ( 16). In contrast with E. coli, the addition of L-Ara4N to lipid A seems to be controlled only by the PmrAB TCSs which activates the arnBCADTEF operon and similarly found in colistin resistant P. aeruginosa isolates, since both strains are not responding the low Mg 2+ Overall, All the strategies employed by Gram-negative bacteria related to the remodeling of LPS either its modification or complete loss of LPS are explained in Table 4 including the genes and operon that responsible for these mechanisms. Pseudomonas aeruginosa to protect these both strains from antimicrobial peptides contributing to polymyxin resistance (182,183). By electrostatic interactions between the anionic of CPS and cationic of polymyxins, release CPS is able to trap or bind to polymyxins leading to the reducing of polymyxin quantity to reach the cell surface of bacteria (183). The significant contribution of CPS to polymyxin resistance compared to the other mechanisms and which genes have been involved is still debated. But interestingly, ugd (also known as pmrE) gene that has a role in L-Ara4N biosynthesis, also known playing a role in UDPglucuronic acid production which is an essential sugar used in the creation of CPS (184).

EFFLUX IN POLYMYXIN RESISTANCE AND OUTER MEMBRANE PROTEIN

Only a few studies have explained the contribution of efflux pumps in polymyxin resistance, such as AcrAB, KpnEF and RosAB efflux pumps. Mutant acrAB (a member of RND multidrug efflux pump family) were significantly more susceptible to polymyxin B compare to the wild-type isolate and reduce the pneumonia incidence in a murine model, as described in K. pneumoniae (185). acrAB genes encode a periplasmic lipoprotein which is important as a bridge the outer and inner membrane for its integration (185). It was similarly shown in the ΔkpnEF (an SMR efflux pump family) mutant of K. pneumoniae that the mutant strains were significantly more susceptible to colistin compare to wild-type strain, and interestingly, exhibit an impairment of capsule polysaccharide synthesis (186). A rosAB (an MFS type efflux pump) mutant in Yersinia enterocolitica with lacking RosA and RosB protein was significantly more susceptible to polymyxin B and these mutations are affecting to the disturbance O-antigen biosynthesis as LPS core oligosaccharide. Generally, efflux pumps prevent the antimicrobial action by pumping the antibiotics out of the cell. However, little is known about the specific role of these efflux pumps in the antimicrobial peptide, including colistin and polymyxin B, but presumably, they play an indirect role in polymyxin resistance.

For the outer membrane porins, their contributions remain still unclear and the involvement of porin in polymyxin resistance might be indirect

POLYMYXIN-INACTIVATING ENZYME

To date, there are two studies that confirm the presence of bacterial enzyme that can inactivate colistin, produced by two Gram-positive bacteria, namely Paenibacillus (bacillus) polymyxa and bacillus licheniformis (190,191). Paenibacillus polymyxa is known as the Gram-positive bacterium that produces colistin but at the same time produce a putative serine protease, referred as colistinase, that able to degrade colistin by cleavage of diaminobutyric acid (Dab-Dab bond) (Table 1) at side chain-cyclic peptide ring (190). While in bacillus licheniformis, it was found that alkaline protease Apr is responsible for colistin inactivation. Apr cleaves between the tripeptide side chain and the cyclic heptapeptide ring, and also between L-Thr and L-Dab in the cyclic heptapeptide ring (Table 1) (191). Although, these proteases have not been associated with colistin resistance in Gram-negative bacteria, it is possible that polymyxins could be digested by secreted protease from other microorganisms, thereby affecting the clinical efficacy of colistin and polymyxin B.

COLISTIN HETERORESISTANCE

Heteroresistance is defined as the condition where subpopulations of bacteria within the same population are showing various responses to antibiotics. In other words, the subpopulations of bacteria that have a higher MIC to a specific antibiotic than most of the population are able to generate detectable colonies with long enough time of culture (192,193). This phenomenon was first introduced in 1947 to describe the heterogenous antibiotic resistance of Gram-negative bacteria Haemophilus influenzae, but the term "heteroresistance" itself began to be used in 1970 (193). Several antimicrobial susceptibility testing methods and standard criteria to define isolates as susceptible, resistant or intermediate to any antibiotic have been developed by several international clinical laboratory standard bodies and are generally agreed worldwide. Unfortunately, the methods to define the heteroresistance that are inexpensive and standardized are lacking.

Furthermore, heteroresistance is different from resistance, persistence and tolerance that are similar phenomena of survival in the antibiotic presence (192). However, both could be differentiated by their surviving profiles after duration longer antibiotic treatment, without a change in the MIC (192).

Emergence of polymyxin heteroresistance was associated with the exposure of suboptimal dosage of colistin (38). Colistin use is known to be a risk factor for the emergence of polymyxin-resistant strains in Gram-negative bacteria and heteroresistant subpopulations were found in the patients that have been previously treated with colistin (194,195). Colistin heteroresistance of A. baumannii isolates is given by the loss of LPS phenotypes displaying high-level colistin resistance (18). Selection by serial increasing concentration of colistin

PLASMID-MEDIATED COLISTIN RESISTANCE

DESCRIPTION OF MOBILIZED COLISTIN RESISTANCE (MCR)

Plasmid-mediated colistin resistance MCR-1 was firstly reported in 2015 in clinical isolates of Escherichia coli and Klebsiella pneumoniae in china, and since, it has been detected all over the world (20,21,134,135,197).

Mobilized colistin resistance (mcr) genes are plasmid-borne phosphoethanolamine

transferases that confer resistance to colistin via phosphoethanolamine-modified bis-phosphorylated hexa-acylated lipid A in E. coli (198) To date, nine known mcr homologues have been identified (mcr-1 to mcr-9) on a numbered different plasmids (199). Since its first report, a large number of studies have been published

on mcr-1 and it is clear that though this gene are undetectable for decades, it has a worldwide distribution and is commonly found in food animals than in humans (198).

Later, a second mcr gene that has been rarely identified, mcr-

PREVALENCE OF mcr-1

Several studies showed that the prevalence of mcr-producing isolates remains comparatively vary in several countries (208). The average prevalence was 4.7% that was reported from 47 countries across six continents (209). A very low prevalence of mcr-1 and mcr-1-producing isolates was found in Switzerland among Enterobacteriaceae isolates from urinary tract infections and there were no mcr-1 positive isolates were found in a large collection of bacteremia isolates in the same country (210, 211). In contrast, up to 50% of mcr-1 positive E. coli isolates were identified from swine with diarrhea and edema in Japan.

In Germany, A high frequency of mcr-1 positive E. coli has been found in food isolates, mainly in turkey (10.7%) and broilers (5.6%) (212). China was reported as the country with the highest number of mcr-1-positive strains with the highest prevalence bacteria was found in E. coli (54%) (209). Still from the same country, the prevalence of pathogenic mcr-1positive E. coli was found higher in food-animal than in humans and food products, suggesting the role of food borne transmission (209). In China, colistin was formally banned from animal feeds since 2017 and only used to human therapy due to the significant increase of mcr-1 prevalence (213).

STRUCTURE OF THE mcr-1 GENE AND PLASMID

A detailed mcr-1 cassette which is also the similar mcr-1 was used in our study is shown in

CLINICAL IMPACT AND IN VITRO STUDY OF MCR-1

Although the emergence of mcr-1 caused global concern, little is known about its clinical implications and its transmission characteristic. Cohort studies focusing on the human infection were rare where the majority of studies were investigating the prevalence of mcr-1-harbouring bacteria. Here, we only found two systematic case-control studies focusing on mcr-1-positive clinical isolates which provide the prevalence, risk factor and effect on mortality (213, 215). A large prevalence study in China detected the mcr-1 gene were only found in E. coli (1%) and K. pneumoniae (<1%) from total 10,688 Enterobacteriaceae, 3,549

Acinetobacter and 3,261 P. aeruginosa clinical isolates of 18,698 inpatients (213).

Interestingly, mcr-1-positive E. coli isolate from healthy patients were also detected (213).

The same study has found that majority of mcr-1 positive E. coli causing skin and soft tissue, Another study shown that 95% of mcr-1 positive E. coli isolate harbored several of resistant genes that may confer resistance to aminoglycosides, sulphonamides, β-lactams, phenicols and fluoroquinolones (215). As shown in Figure 14, compare with small plasmids, such as IncX4 or IncI2, large plasmid encoding mcr-1 IncHI2 are able to recruit other resistance genes and become multiply drug-resistant, which could raise the difficulties of treatment ( 215).

An in vitro study of mcr-1 effects on colistin resistance and on lipopolysaccharide structures of Gram-negative pathogens have found that PEtN modifications of lipid A was observed in all four species E. coli, K. pneumoniae, A. baumannii, and P. aeruginosa after mcr-1carrying recombinant plasmids were successfully introduced into laboratory and clinical isolates tested (198). It led to high-level colistin resistance in E. coli, K. pneumoniae and A. baumannii but only moderately resistance in P. aeruginosa (198).

The mcr-1 confers their colistin susceptibility and increased colistin MIC up to 32-fold, 256fold, >128-fold and 4-fold in E. coli, K. pneumoniae, A. baumannii, and P. aeruginosa, respectively (198). This indicates that native promotor of mcr-1 found in E. coli is not only functionally across diversified species among Enterobacteriaceae, such as K. pneumoniae, but also the other two species tested, including A. baumannii and P. aeruginosa (214). This also suggest that K. pneumoniae and A. baumannii would be acquiescent to mcr-1 that may confer them into high-level colistin resistant pathogens compare to E. coli as its original reservoir, and moreover, this dissemination across species could be a threat to manage in the future.

LITERATURE REVIEW PK/PD of Antibiotics

IV. PK/PD OF ANTIBIOTICS

In general, pharmacokinetic (PK) is defined as "how the body handles the drug", while pharmacodynamics is "how the drugs affects the body". But in terms of bacterial killing, PD would be more adequately phrased as "how the drug affects the bacteria" (217). PK/PD of antibiotics differ from other drugs, where the ideal antibiotic is targeting the bacteria instead of directly affect their host and cause side effects. In PK/PD modeling, the relationship among dose, concentration, desired effect and side effects is described and quantitated, and this approach is used in the development and improvement of antibiotic dosing regimens (217).

MIC-BASED APPROACHES

For many years, the MIC has been used extensively for determining bacterial susceptibility to an antibiotic. Agar diffusion or broth dilution are two methods most used on MIC test since they are easy to perform. In general, broth dilution method is used to determine MIC of antibiotics, by inoculated a bacterial inoculum of 5 x 10 5 CFU/mL into specific media with a range of the antibiotic concentrations based on two-fold dilution, at 37 °C, over 18-24h incubation period (220).

The relationship between drug exposure and MIC is a primary basic on this PK/PD approach with three standard PK/PD indices have been determined; fT>MIC; fCmax/MIC; and fAUC/MIC f refers to the free drug concentration. The duration of time in the 24-h period wherein the drug concentration above the MIC is fT>MIC. Cmax is the peak drug concentration. AUC refers to the area under drug concentration-time curve over the 24-h. These indices are based on free drug concentration, where only the unbound drug can exert its pharmacological effect. If the efficacy is time dependent, the goal is to maintain the free drug concentration above the MIC for an extended period of time. But, if the effect is concentration dependent, the dosing strategy is simply to attain sufficient Cmax or drug exposure above MIC (221).

Though MIC has been used to guide dosing for various classes of antibiotics, this approach has several limitations (220). First, it is a static parameter evaluated only which is not possible to characterize the effectiveness of an antibiotic when its concentrations change over time. Not only potentially lead to treatment failure, when bacteria are exposed to a low concentration of antibiotics, it may foster the emergence of resistant populations. Second, the MIC may not be consistent across the species and strains which is also possibly lead to treatment failure.

IN VITRO TIME-COURSE-BASED APPROACHES: TIME-KILL KINETIC STUDIES

The in vitro time-kill (TK) offers unique opportunities to characterize bacterial response versus time after multiple-dosing of antibiotic exposure (217). Time-kill experiments has been used to generate in vitro data in static conditions, as the basis for developing antibiotics PK/PD models that links of free drug concentration to the bacterial response, whereas dynamic (hollow-fiber) time-kill data, that supposedly to mimic the in vivo half-life of the drugs in humans, are used to validate the model and to predict the clinical outcome (220). Basically, antibiotic PK/PD models are driven by in vitro data with 3 following models:

bacterial submodel, pharmacokinetic model, and the full model combined from PK and bacterial submodel (PK/PD model).

BACTERIAL SUBMODEL (PHARMACODYNAMIC MODEL)

Bacterial submodel is characterized by the growth and natural killing of the bacteria versus time which involves a single bacterial compartment (B) with a first-order rate constant for bacterial multiplication (kgrowth) and a first-order rate for the death of bacteria (kdeath).

𝑑𝐵 𝑑𝑡 = 𝑘 𝑔𝑟𝑜𝑤𝑡ℎ x 𝐵 -𝑘 𝑑𝑒𝑎𝑡ℎ x 𝐵 (1)
Equation (1) explains the observed exponential growth of bacteria seen in time-kill experiments without the addition of drug (217). In the absence of antibiotics, the exponential grow will be shown until high concentrations of bacteria are reached and stationary level is approached.

PHARMACOKINETIC MODEL

PK describes the change of antibiotic concentration (C) over time (t) during the experiment.

In static time-kill, the antibiotic concentration is commonly expected constant. But some drugs show instability under the experimental conditions and the concentration is estimated to decline from an initial concentration (C0) and can be determined using one-compartment PK model.

𝐶 (𝑡) = 𝐶 0 𝑥 𝑒 -𝑘 𝑒 x 𝑡 (2)
ke represents elimination rate constant and the half-life (t1/2) can be determined using ke,

where 𝑡 1/2 = ln(2)

𝑘 𝑒

The elimination rate constant can also be derived from volume of distribution (Vd) and clearance (𝐶𝑙), where 𝑘 𝑒 = 𝐶𝑙/ 𝑉 𝑑 Due to more complex distribution and drug disposition, time-kill profile should be better described by two-compartmental model with a central and a peripheral compartment. When antibiotic concentration is measured, the parameters of PK model can be estimated and predicted concentrations can be used to drive PK/PD model.

PHARMACOKINETIC-PHARMACODYNAMIC MODEL

The bacterial submodel and the PK model are combined to drive the full PK/PD model, and equations are determined to characterize the antibiotic effects on the bacteria. Antibiotic effect is modeled using Emax. The antibacterial effect could be assumed either to inhibit the bacterial growth rate (Eq. 3) or to enhance the bacterial kill (Eq. 4 and 5). The effect can be modeled as a proportional effect (Eq. 4) or an additive effect (Eq. 5). adaptive resistance (Fig. 16). In case of pre-existing resistant bacterial subpopulation, two different bacterial compartments representing antibiotic sensitive (S) and resistant (R) should be assumed. In case of appearance of adaptation phenomena, an adaptive resistance (AR) is modeled using a binding function with two states, adaptive resistance being off and being on. In a simple word, the AR was set to off, but the increasing of antibiotic concentrations might increase the degree of resistance. In the static time-kill experiments, PD models with two stable heterogenous subpopulations (S/R) are most often demonstrate superiority over models relying on adaptation phenomena (222). Although these models should be validated in dynamic conditions (i.e., hollow-fiber), these experimental handling are more complex and expensive compare with time-kill experiments. Therefore, in this study, we offer a new approach, namely sequential TK, to discriminate between PK/PD models with S/R versus adaptive resistance. It is expected to be a simple and inexpensive approach to generate.

𝑑𝐵

PROBLEMS AND OBJECTIVE OF THE STUDY

As explained in the previous chapter, the emergence of multi-drug resistance of Gramnegative E. coli, K. pneumoniae, and A. baumannii over the last-resort antibiotic polymyxins is increased (17,38). Isolates obtained before and after colistin treatment demonstrated that colistin use correlated with increased resistance to polymyxin (223). Moreover, colistin heteroresistance subpopulation isolates were particularly found in the patients that previously treated with colistin (18,194). The chromosomal genes involved in the mechanisms of polymyxin resistance have been established. However, the influences of plasmid harboring mcr-1 gene, particularly carried by E. coli and K. pneumoniae, to induce additional genomic resistance and to facilitates the selection of high-level polymyxin resistance is poorly described. In another story, instead of by mcr-1 helping, Acinetobacter baumannii is adding a different strategy to protect themselves from damage caused by polymyxins via completely losing its lipid A as the initial binding target of polymyxins (19,170). Again, how this strain acquired polymyxin resistance during treatment is poorly understood.

In vitro static time-kill (TK) is a simple pharmacodynamics (PD) experiment to simulate bacterial CFU versus time after the multiple-dose of antibiotic exposures. This is a simple and inexpensive approach to evaluate the rate and extent killing due to of colistin and polymyxin B against Gram-negative bacteria. After an initial decay of CFU, a regrowth is frequently observed thereby time-kill data were often used for PD model qualification with two stable heterogenous subpopulations model, i.e., sensitive (S) and resistant (R), which often demonstrate over drug induced adaptive resistance (AR) model ( 222). Since no precise mechanistic information provide by this approach, these models could be challenged by dynamic (hollow-fiber) conditions, but these experimental handling are more complex and expensive than TK experiments.

Therefore, we offer an alternative by performing two consecutive time-kill (referred to as "sequential TK") to discriminate between the bacterial regrowth due to heterogenous subpopulations (S/R) or adaptive resistance (AR). After the (R) selection and (S) disappearance during the first TK, the (R) subpopulations are supposed to be stable with time without any regrowth after a second TK is conducted. Otherwise, a second regrowth would rather suggest a continuous adaptation with time. To provide the molecular information, these experiments will be supported by biomolecular investigations, including DNA sequencing and quantitative PCR, to observe nucleotide changes (mutations) and to analyses the expression level of the specific target gene.

Overall, these studies have been divided in three parts:

1. First step, we confirmed experimentally that sequential TK could discriminate between stable heterogenous subpopulation (S/R) and a single homogenous population of bacteria without or with adaptive resistance (AR) demonstrated by pharmacokinetics/pharmacodynamics (PK/PD) models. Modelling was conducted after the first TK and then simultaneously after sequential TK to compare the prediction models between a single and sequential TK analysis.

2. By using the sequential TK approach, we determined the molecular impact of MCR-1 in the progressive adaptation of E. coli and K. pneumoniae to polymyxins by characterizing the chromosomal genes involved in lipopolysaccharide modification.

3. With similar approach, we characterized the genes involved in polymyxin resistance, cation-adjusted Mueller-Hinton broth over 30 h at an initial inoculum close to 10 6 CFU/ml in the presence of polymyxin B (PMB) ranging from 0.0625 to 1 mg/liter for KP_WT and 0.5 to 8 mg/liter for KP_MCR-1. At 30 h, bacteria that regrew up to 10 8 CFU/ml were harvested by centrifugation and resuspended to immediately begin the second TK experiment at an initial inoculum close to 10 6 CFU/ml again, with PMB concentrations ranging from 0.0625 to 1 mg/liter for KP_WT and 1 to 32 mg/liter for KP_MCR-1. Modeling was conducted after the first TK and then simultaneously after the two sequential TK experiments for both strains, using NONMEM 7.4 with Laplacian numerical algorithm and the M3 method for handling observations below the limit of quantification (4). Each model incorporated a logistic growth expression to describe bacterial population dynamics. PMB bactericidal effect was modeled according to an Emax function for both strains. Two different model structures were investigated to characterize the emergence of resistance. The first model, S/R, includes two independent subpopulations of bacteria with different susceptibilities and regrowth explained by a higher EC50 (concentration that produces 50% of Emax) value for the (R) than the (S) subpopulation (Fig. 1A) (5-7). The fraction of (S) and (R) bacteria in the initial inoculum was estimated as a parameter, and fitness cost resulting in a lower growth rate for the (R) subpopulation was investigated. The second model, AR, includes a single homogenous bacterial population with adaptive resistance (Fig. 1B). At the beginning of the experiment, all bacteria were assumed to be nonadapted, but an adaptation developed over time in the presence of PMB, affecting Emax (8). The fraction of (S) and (R) or adapted bacteria, depending on the model, at the end of the first TK experiment was used as the initial condition for the second TK experiment. Model selection was based on objective function value and goodness-of-fit plots. For nonnested models, the Bayesian information criterion (BIC) was calculated and compared between models. Genes assumed to be involved in polymyxin resistance, i.e., pmrA, pmrB, phoP, phoQ, pmrC, pmrE, lpxM, arnT, cptA, lpxT, eptB, and mcr-1, were sequenced. Expression was analyzed by real-time quantitative PCR (RT-qPCR) and analyzed with the 2 -ΔΔCT method, by normalizing the relative expression of selected genes to the expression of rpsL used as an internal control (9), to determine their expression levels before and after the first and second TK experiments for both strains.

either
An initial CFU decay followed by regrowth was observed in both strains after the first single TK experiment, at PMB concentrations of 0.125 mg/liter for KP_WT and 1.0 and 2.0 mg/liter for KP_MCR-1 (Fig. 2). The S/R and AR models provided relatively good data fitting, although, as expected, statistical comparisons favored the S/R model (see BIC values in Table 1) (2). However, differences were observed between strains during the second TK experiment. In the presence of KP_WT, PMB apparent activity was slightly FIG 2 Comparison of predictions from the S/R and AR models after analysis of a single TK experiment (A) or after simultaneous analysis of the sequential TK data (B) for 2 isogenic isolates. (Top) K. pneumonia R2292 (KP_WT); (bottom) its MCR-1 transconjugant (KP_MCR-1). For KP_WT, PMB concentrations ranging from 0.0625 to 1 mg/liter were used for the 2 sequential TK experiments. For KP_MCR-1, PMB concentrations ranging from 0.5 to 8 and 1 to 32 mg/liter were used for the first and second TK experiments, respectively. Symbols, experimental data (n = 2); color-matched lines, model predictions; gray solid lines, limit of quantification.

reduced, no initial CFU decay was observed at a concentration of 0.125 mg/liter anymore, but no regrowth was observed after the rapid decay observed at 0.25 mg/ liter, consistent with (S) and (R) stable heterogeneous subpopulations (Fig. 2B, top). Accordingly, the S/R model was still able to describe the experimental data after simultaneous analysis of the two sequential TK experiments and to quantify the phenotypic difference between the two subpopulations with precision, with the reduced apparent activity for the (R) population reflected by an EC50 value (EC50,R) that was slightly higher than that for the (S) population (EC50,S) (0.132 versus 0.065 mg/liter). In contrast, with KP_MCR-1, regrowth was observed at concentrations of 1 and 2 mg/ liter after the first TK experiment and again after the second TK experiment, but at slightly higher concentrations of 4 and 8 mg/liter (Fig. 2B, bottom), indicating that PMB continued to lose efficacy during the second TK experiment. This sustained changing activity with time is not consistent with a stable (R) subpopulation but rather suggests continuous adaptation with time. Only the AR model was able to provide a relatively good fit of these sequential TK data for KP_MCR-1.

However, these models were not really supported by RT-qPCR investigations. No mutation was observed with KP_WT to support the two heterogeneous subpopulations for the S/R model. With KP_MCR-1, an overexpression was observed for the mcr-1 gene but with the same magnitude (5.5-fold) at the end of the first and second TK experiments compared with time zero, which is not consistent with continuous progressive adaptation during the first and second TK experiments. In this study, only two simple models, representative of the two basic situations, i.e., stable heterogeneous subpopulations (S/R) versus unstable homogenous population (AR), were tested. Although they provided relatively good fit, these models were not supported by the mechanistic experiments, suggesting that real life is likely to be more complex, with combined heterogeneity and instability issues requiring more complex models (1). Furthermore, mutant selection or adaptation phenomena may occur slowly and only be observable after several days of hollow-fiber experiments, which remain the most demanding but best approach for in vitro semimechanistic PK/PD modeling of antibiotics (10)(11)(12). Yet, although this study suffers from limitations, it shows that sequential TK experiments The sensitive (S) and resistant (R) subpopulations were assumed to grow at different rates, with the estimation of 2 different Kg for (S) and (R) resulting in a significant decrease in the objective function value given by NONMEM. d The Hill coefficient for this relationship, initially estimated to fall between 10 and 20, was fixed to 10 to improve model stability (13). e PMB bactericidal effect was modeled using an ordinary Emax model, with the estimation of Hill coefficient resulting in a nonsignificant decrease in the objective function value given by NONMEM. f Kon was estimated in the presence of PMB but was not dependent on its concentration. g The resistance onset rate was determined by the PMB concentration through a sigmoid Emax model. Kon corresponds to the maximal rate constant for development of AR in this case.

constitute a simple approach to disqualify S/R models selected after traditional TK experiments and that these S/R models should not be used without further validation to predict treatment outcomes after multiple dosing.

INTRODUCTION

The increasing prevalence of multidrug-resistant Gram-negative bacteria infections and the absence of novel antibiotics have forced physicians to re-evaluate 'the old' antibiotics such as colistin, to be used as last resort drugs (1)(2)(3)(4). Unfortunately, Gram-negative bacteria are able to develop several strategies to protect themselves from damage caused by polymyxins (5). During time-kill (TK) experiments, regrowth are frequently observed after few hours, attesting for an apparent loss of antimicrobial activity with time. These regrowth can be described by the so-called S/R model comprising two heterogeneous subpopulations, sensitive (S) and resistant (R), with antimicrobial susceptibility constant with time, or by a variety of adaptive models with a single homogeneous population with sensitivity changing with time. Unfortunately, model discrimination is very difficult after traditional TK experiments, and simulations have shown that the S/R model is likely to be selected even using data generated with an adaptation model ( 6). Yet conducting two TK experiments consecutively would allow differentiation between S/R and adaptation models, as recently done to characterize the rapid decrease of polymyxin B activity against a Klebsiella pneumoniae strain bearing MCR-1 (7). Although this approach presents limitations, it can be easily applied to provide cheap and quick information. The objective of this new study was first to confirm the potential of this innovative approach with colistin, and second to characterize the mechanism responsible for this rapidly developing adaptive resistance of polymyxins in Klebsiella pneumoniae strain bearing MCR-1.

RESULTS

Without previous exposure to CST, MIC against KP_MCR-1 was 8-fold higher than against KP_WT, and noticeably MICs against KP_MCR-1 estimated at the end of the 1 st and 2 nd TK were considerably increased, but unchanged against KP_WT (Table 1).

Sequential time-kill experiments

TK results (Fig. 1) are consistent with observations made by comparing MICs. First, they confirm the reduced initial CST antimicrobial activity against KP_MCR-1 by comparison with KP_WT, as clearly evidenced for example by comparing the results obtained during the 1 st TK with a CST concentration equal to 1 mg/L (Fig. 1A and1C). Second, they confirm that CST antimicrobial efficacy against KP_WT is basically unchanged after the 1 st and then 2 nd TK, as clearly illustrated at a concentration of 0.125 mg/L (Fig. 1A and1B), whereas the activity against KP_MCR-1 decreases dramatically between the 1 st and 2 nd TK, as can be seen at CST concentrations of 4 or 8 mg/L (Fig. 1C and1D). Accordingly, KP_WT data were best fitted using a simple PD model with only one homogenous population of bacteria with CST activity unchanged with time (Fig. 2A), whereas an adaptation model (AR) (Fig. 2C) best described KP-MCR-1 TK data. In both cases a time delay function improved data fitting. Parameters values are presented in Table 2.

Genes expression

No mutation was found in LPS-modifying genes at the end of the 1 st and 2 nd TK compared to the respective initial strain KP_WT and KP_MCR-1 (data not shown). Initial expression of LPS-modifying genes did not differ significantly between KP_WT and KP_MCR-1, and gene overexpression after exposure to CST was only observed with KP_MCR-1 (Fig. 3).

Apart from mcr-1 that was up-regulated by more than 5-fold at the end of the 1 st and 2 nd TK, 3 genes (cptA, eptB and lpxT) seemed to be moderately down-regulated only at the end of the 2 nd TK , and 3 genes (pmrA, pmrC and pmrE) were transitorily up-regulated by more than 5-fold at the end of the 1 st TK. Yet the most spectacular overexpression was observed with arnT that was up-regulated by more than 20-fold at the end of the 1 st and 2 nd TK (Fig. 3).

DISCUSSION

These new results obtained with CST are essentially consistent with those previously published with polymyxin B using the same K. pneumoniae strain and experimental setting (7). Yet because KP_WT susceptibility to CST was unchanged between the 1 st and 2 nd TK, a simple PD model with a single population and no effect of time on antimicrobial efficacy, was sufficient to describe the data, instead of the model S/R with two sub-populations (S/R) previously used with polymyxin B (7). Furthermore, in agreement with this single population model, no mutations in LPS-modifying genes were observed and no resistant subpopulations were detected with PAPs (data not shown). Another minor difference with the previous study (7), is that the modeling was slightly improved by incorporating a delay in the growth of the bacteria, related to the fact that bacteria were not in their logarithmic growth phase at time 0 (8).

Yet this new study shows that whereas the presence of the mcr-1 gene induces a relatively modest decrease of the initial susceptibility to CST for this particular strain of K.

pneumoniae, as previously reported by Nang et al. (9), it is responsible for pronounced adaptive resistance leading to high-level CST resistance, not observed with KP_WT. Since the KP_MCR-1 strain is a transconjugant strain with a MCR-1 plasmid of E. coli origin (10), this result indicates that native promotor of mcr-1 found in E. coli is functional across diversified species among Enterobacteriaceae, such as K. pneumoniae, as similarly shown in a previous in vitro study (11).

Among differences in the expression of LPS-modifying genes during CST exposure, a relationship seems to exist between arnT overexpression leading to an addition of 4-amino-4-deoxy-L-arabinose (L-Ara4N) on the lipid A of the LPS (12), and decreased susceptibility to CST observed in KP_MCR-1. ArnT protein upregulation due to two-component systems PmrA/B and PhoP/Q activation is responsible for CST resistance in most clinical K.

pneumoniae isolates ( 13), and the level of this upregulation dictates CST MICs, consistent with our results (14). Regarding polymyxin resistance, the LPS modification by L-Ara4N addition confers higher level of resistance than phosphoethanolamine (PEtN) modifications only, which increased the resistance up to 250-fold in the mutant expressing L-Ara4N (15,16).

Our results suggest that the expression of mcr-1 could facilitate another mechanism like L-Arabinose addition to LPS depending of arnT overexpression under CST pressure, which is different from a previous study showing that arnT is overexpressed only on K. pneumoniae clinical isolate deleted for mcr-1 exposed to polymyxin B but not in the presence of mcr-1 gene (17).

However, regulation of polymyxin resistance in K. pneumoniae is complex, since PmrA/B and PhoP/Q can directly activate the arn operon, which is usually controlled only by PmrA/B as observed in E. coli and P. aeruginosa (18)(19)(20). In this study, differences in the expression of phoP/Q were weak and other genes like cptA (a PEtN transferase), lpxT (phosphorylates lipid A) and eptB (a PEtN transferase) were down-expressed in KP_MCR-1 during sequential TK. As previously described in mgrB mutant (14,21), other genes like pmrC and pmrE have a minor role in CST-resistant K. pneumoniae compared to the modification of LPS by arn operon.

Although previous studies have shown emergence of mutations after contact with CST in the presence of mcr-1 in E. coli (22,23), no mutation was found in LPS-modification genes in this study. Thus, additional mutations and/or differences in the expression of other genes are not to be excluded and could be investigated for further studies by "-omics" approach like next generation sequencing or RNAseq methods.

From a dynamic standpoint, the reduction of CST antimicrobial activity against KP_MCR-1 with time can first be appreciated by comparing initial MICs values, higher for KP_MCR-1 (2 mg/L) than for KP_WT (0.25 mg/L), but unchanged after the 1 st and then 2 nd TK in the case of KP_WT, and dramatically increased at the end of the 1 st and then 2 nd TK with KP_MCR-1, attesting for rapid loss of antimicrobial activity (Table 1). Yet due to geometric dilutions, at such high values, MICs do not provide a precise estimate of antimicrobial susceptibility. Furthermore, MICs correspond to averaged values over a 24h period of time and therefore do not reflect antimicrobial activity at a specific time-point, as would be required when adaptive resistance occurs quickly. PD modeling offers better characterization of the effect of mcr-1 expression on the rapid loss of K. pneumoniae susceptibility with time and illustrates some potential consequences in terms of dosing regimen optimization.

The AR model (Fig. 2C) predicts that CST antimicrobial efficacy decreases with time as a consequence of an increased percentage of ARon (% ARon) bacteria (and corresponding decreased percentage of ARoff). In order to better capture this changing antimicrobial activity with time and make that change more explicit, we have defined an "instantaneous MIC" (MICinstant). This corresponds to the CST concentration at which CFU would change from 5x10 5 to 10 7 log CFU/mL, over 24h, for any given percentage of ARon (and therefore ARoff). The relationship between MICinstant and %ARon is shown on Fig. 4A. At time zero, when ARoff = 100% and therefore ARon = 0, MICinstant, is equal to 1.5 mg/L, consistent with and slightly lower than 2 mg/L, the experimentally determined MIC over 24h.

Noticeably the initial increase of MICinstant with %ARon is relatively slow from 1.5 to 3 mg/L when %ARon increases from zero to 50%, and until %ARon reaches approximately 75%-80% when an abrupt increase of MICinstant is observed (Fig. 4A). The AR model can also predict the variation of %ARon with time, and because this is affected by CST concentration, we have chosen to conduct these simulations (Fig. 4B) at a CST concentration corresponding to the experimentally determined MIC (2 mg/L). It appears that %ARon increase with time is not linear but the corresponding curve flattens down with time, with %ARon being close to 50% after 24h and to 75% after 48h. Eventually these two curves (Fig. 4A and4B) can be combined to predict the variation of MICinstant with time (Fig. 4C). In order to be consistent with previous Figures, these new simulations have been conducted again for a CST concentration equal to 2 mg/L. Consistent with the initially slow and then rapid increase of MICinstant with %ARon (Fig. 4A), MICinstant increases more rapidly at later times (from 3 mg/L at 24h to 8 mg/L at 48h) than at early times (from 1.5 mg/L at time zero to 3 mg/L at 24h). However, the late MICinstant versus time profile (Fig. 4C) is less abrupt than the MICinstant versus %ARon one (Fig. 4A) due to the fact that %ARon increases less proportionally than time (Fig. 3B). These MICinstant values must be interpreted carefully as they are derived from a model that properly described sequential TK data, but which is obviously an oversimplification of a more complex realty. These results obtained in static In conclusion, this study has shown that adaptive resistance to CST occurs in a Klebsiella pneumoniae strain carrying the mobile colistin resistance (mcr) gene MCR-1 but not in the control strain. From a mechanistic standpoint this decreased susceptibility to CST should mostly be due to arnT up-regulation. From a dynamic standpoint, the PD model with adaptation that successfully described the experimental data, suggests that the reduction of CST antimicrobial activity should initially be progressive before becoming very rapid.

Because of its potential major consequences in clinical practice, this observation should be confirmed and possibly refined, in different experimental conditions.

MATERIALS AND METHODS

Bacterial strain. Colistin-susceptible Klebsiella pneumoniae R2292 wild-type (KP_WT), and its isogenic MCR-1 transconjugant strain carrying the mobile colistin resistance (mcr) gene MCR-1 (KP_MCR-1) were kindly provided by P. Nordmann (University of Fribourg, Switzerland). Their construction process was described previously (10).

Antimicrobial susceptibility assays. Colistin (CST) MICs against KP_WT and KP_MCR-

1 were determined at time zero and at the end of the first time-kill (30h) and second timekill (60h). by microdilution methods in cation-adjusted Mueller-Hinton broth (MHB-CA)

according to joint CLSI -EUCAST protocol (24) and results were interpreted using EUCAST guidelines (25).

Sequential time-kill (TK).

Individual tubes of 15 mL of MHB-CA containing CST at concentrations ranging from 0.0625 to 1 mg/L for KP_WT and 0.5 to 8 mg/L for KP_MCR-1 were inoculated with the bacterial suspension (~ 1*10 6 CFU/mL) and incubated at 35° ± 2°C, under shaking conditions (150 rpm) up to 30 hours. Bacteria were quantified at 0, 1, 3, 8, 24 and 30 hours by spiral plating on MH agar plates after appropriate serial dilutions (Interscience ® spiral). CFUs were enumerated with an automatic colony counter (Interscience Scan 300) after 24 hours of incubation at 37°C. The theoretical detection limit was 200 CFU/mL i.e. 2.3 log10 CFU/mL. After the 1 st TK (at 30 h), bacteria that regrew up to 10 8 CFU/mL in the presence of antibiotic were harvested, washed out and then reinoculated at 10 6 CFU/mL as initial concentration to perform the 2 nd TK with CST concentrations ranging from 0.0625 to 1 mg/L for KP_WT and 2 to 64 mg/L for KP_MCR-1.

Population analysis profiles (PAPs).

One hundred µL of bacterial cell suspension (used for inoculation) were plated on Mueller-Hinton agar plates containing various CST concentrations (0, 0.125, 0.25, 0.5, 1, 2, 4, 8, 10, 16 mg/L) after serial dilutions as described previously (26). CFUs were enumerated as described before.

RT-qPCR. Expression of lipopolysaccharides-modifying genes involved in polymyxin

resistance (pmrA, pmrB, phoP, phoQ, pmrC, pmrE, lpxM, arnT, cptA, lpxT and eptB) and mcr-1 were analyzed quantitatively by Two-step Real-Time PCR method. Initially, RNAs of KP_WT and KP_MCR-1 isolates, isolated before and after consecutive TK, were extracted and purified. Then, quantity and purity of RNA were determined and reverse transcription (RT) was performed starting from 2 µg of isolated RNA. cDNA template was diluted one tenth in PCR grade water. qPCR was done using the specific primers (Table S1).

Then, 20 µL of the real-time PCR mixture were analyzed and relative expression of genes was normalized to the expression of housekeeping genes rpsL by 2 -∆∆CT method. Genes differentially expression were analyzed with the criteria threshold of twofold change (27,

28)

PCR amplification and sequencing. The pmrA, pmrB, phoP, phoQ, mgrB, arnT, and pmrC genes involved in polymyxin resistance were amplified using specific oligonucleotides (Table S1). The amplified DNA fragments were purified and were processed by Sanger sequencing. Genomic DNA of all isolates was visualized and identified using SnapGene software (v3.1.1).

PD modeling. Sequential TK curves were simultaneously analyzed using NONMEM 7.4

with Laplacian numerical algorithm and the M3 method for handling observations below the limit of quantification (29). Three models were compared to fit TK curves data obtained with KP_WT and KP_MCR-1: one with a single homogenous population and no adaptation for data fitting in the absence of regrowth (Fig. 2A), and two others including either two independent subpopulations with different antibiotic susceptibilities (S/R model, Fig. 2B) or a single homogenous bacterial population with adaptive resistance (AR model, Fig. 2C) for data fitting in the presence of regrowth, as previously done with polymyxin B (7). However, the previous models were slightly improved by incorporating a delay in the growth of the bacteria. Details and equations of these in vitro PD models are available in the Supplementary Material.

Simulations. Instantaneous MIC (MICinstant) for any given percentage of ARon (%ARon=

ARon /(ARon + ARoff)), was defined as the CST concentration at which CFU would change over 24h from 5x10 5 to 10 7 CFU/mL assumed to be the lowest number of micro-organisms that can be detected visually (i.e. results in cloudiness) for most common bacteria (30). The

K. pneumoniae RT-qPCR rpsL F TGCGTAAAGTTTGCCGTGTG (1, 2) rpsL R GCC GTA CTT GGA GCG AGC CTG pmrA -F GAT GAA GAC GGG CTG CAT TT (3) pmrA -R ACC GCT AAT GCG ATC CTC AA pmrB -F CTGCCAGCTGATAAGCGTCTT (3) pmrB -R TTCTGGTTGTTGTGCCCTTCG PhoP -F ATTGAAGAGGTTGCCGCCCG (1) PhoP -R GCTTGATCGGCTGGTCATTCACC PhoQ -F TATGCTGGCGAGATGGGAAAACG (1) PhoQ -R CAGCCAGGGAACATCACGCT pmrC -F GGTTTTGGCGGTATTCGTCG This Study pmrC -R CACAATGCTGTTGGAAGGGC pmrE -F CCCTGTTTACCGACTCCACC This Study pmrE -R ACCAAAGGACGGGTTGTTGT arnT -F CCGCTCAATTTCCGTTTGCT This study arnT -R AACCGGCAATCGGTTTTTCG cptA -F GTTTTCCCTGCTGCTTCACG This study cptA -R AGTTTTATCTCCCCGCGACG lpxT -F CGACGTCGTTAACTTCCCCACT This study lpxT -R GCGGGAAAGCAAAGACCACAA eptB -F GCTGGTTTATGAACGTCGCC This study eptB -R TCACCGAAGCGATAATCCCG lpxM -F CAAACTCGGTCGTCTGGTAGG This study lpxM -R GGGCAAGGATTTTCTGCGGAT Sequencing pmrA -F CGCCATGTAGAGAGGCTGGTT This study pmrA -R AGTTGCAAACAGAGCCATGGTC pmrB -F ACC TAC GCG AAA AGA TTG GC (3) pmrB -R GAT GAG GAT AGC GCC CAT GC phoP -F TGCTAGGGAGAACAGCCATGC This study phoP -R CGGGAAGATATGCCGCAACAG phoQ -F1 ATACCCACAGGACGTCATCACC (3) phoQ -R1 CGAGTGGTGTTGGGATTGAGC phoQ -F2 GCGCGAACTGGAGGAACATC phoQ -R2 CTGCAGGTGTCTGACAGGGATTA mgrB -F GGTTTAAGAAGGCCGTGCTATCC (3) mgrB -R GAAGGCGTTCATTCTACCACCC arnT -F1 CTGGCTCGGACGTGAACAATT this study arnT -R1 TGTAGTACCAGAACGGCGCTT arnT -F2 AGCGTTTTGCTGAAAAAGACGC arnT -R2 CCTGTTTCTGGCAGAGCTGTC pmrC -F1 AATAGGGCTGGCACTATACCCT pmrC -R1 CACAATGCTGTTGGAAGGGC pmrC -F2 ACAAAGAGCTGGTGAAATCCCTG this study pmrC -R2 ATTAACCCCTGCAACAGCAGC

Pharmacodynamic model

Bacterial growth sub-model

A logistic growth model (4, 5) with one compartment for each bacterial subpopulation was used to describe the in vitro bacterial population dynamics. An empirical first-order rate constant (β) was estimated to characterize the observed delay in the growth of the bacteria (6) according to:

𝑑𝐵 𝑛 𝑑𝑡 = 𝐾𝑔 × (1 -𝑒 -𝛽×𝑡 ) × (1 - 𝐵 𝑡𝑜𝑡 𝐵𝑚𝑎𝑥
) × 𝐵 𝑛 (Equation 1)

𝐵 𝑡𝑜𝑡 = 𝐵 1 + 𝐵 2 + ⋯ + 𝐵 𝑛 (Equation 2)
Where n is the number of bacterial subpopulations, Bn (CFU/mL) is the n-th bacterial subpopulation, Kg (h -1 ) is the apparent growth rate constant, β (h -1 ) the rate constant characterizing the growth delay and Bmax (CFU/mL) the maximum bacterial count reached in the system. Parameters related to the bacteria growth (Kg, β and Bmax) were first estimated using only the control data and then fixed for the estimation of the parameters related to the antimicrobial effect of CST and development of resistance.

Drug effect sub-model

The logistic growth model was modified to incorporate colistin bactericidal activity, such as:

𝑑𝐵 𝑛 𝑑𝑡 = 𝐾𝑔 × (1 -𝑒 -𝛽×𝑡 ) × (1 - 𝐵 𝑡𝑜𝑡 𝐵𝑚𝑎𝑥 ) × 𝐵 𝑛 -𝐾 𝐶𝑆𝑇 × 𝐵 𝑛 ( Equation 3

Characterization of lipopolysaccharide-modifying genes involved in polymyxin resistance in Escherichia coli carrying MCR-1 by sequential time-kill approach

Hariyanto Ih 1, 3 , Nicolas Grégoire 1, 2 , Sandrine Marchand 1, 2 , William Couet 1, 2 , Julien M. Most of these LPS modifications has been identified being encoded chromosomally involving a large panel of genes and operons regulated by PmrA/PmrB and PhoP/PhoQ twocomponent systems (3). The activation of these regulatory LPS-modifying genes are triggered by environmental stimuli and specific mutations that result in the alteration of their expression (4-6). The chromosomal genes involvement is known since decades as a primary mechanism inducing polymyxin resistance until it was recently reported that it can also be caused by horizontal gene transfer (7)(8)(9). First found in 2011 in Escherichia coli from animal isolates, plasmid-mediated colistin resistance MCR-1 (mobile colistin resistance) in E. coli from human isolates was reported in 2015, and thence forward it have been detected all over the world (10,11). It was reported in E. coli study that plasmid harboring mcr-1 gene mediated polymyxin resistance induced the addition of PEtN on lipid A (12,13). The MCR-1-positive isolates usually exhibited a low-level colistin resistance with MIC values of 2 to 8 mg/L (14,15). However, if MCR-1 plasmids are known to induce low-level of resistance to polymyxins that could probably limit the risk for therapeutic dead end, the influence of this plasmid to induce additional genomic resistance and potentially high-level of polymyxins resistance is poorly described. The aim of this study is to characterize, by an original approach of sequential time kill curves developed recently (16), the role of MCR-1 in the development of additional adaptive resistance mechanisms leading to high-level polymyxin resistance in E. coli. This study provides the molecular impact of the MCR-1 presence during time kill studies against colistin and polymyxin B towards chromosomal genes involved in lipopolysaccharide modification.

RESULTS

MCR-1 is associated with increasing resistance of E. coli during consecutive colistin and polymyxin B exposure

During sequential time-kill, a rapid decay followed by a regrowth was observed during first TK with concentrations below 0.125 mg/L for wild-type E. coli J53 exposed to colistin (CST) or polymyxin B (PMB) (Fig. 1A and1C). No initial decay was observed during second TK, then a rapid regrowth was observed at a concentration 0.125 mg/L in CST and PMB.

In contrast to wild-type strains, E. coli carrying MCR-1 (EC_MCR-1) showed an adaptation during the exposure to polymyxin antibiotics (Fig. 1B and1D). The TK profile is however comparable with its wild-type strains with an initial rapid decay then a regrowth for concentrations close to the initial measured MIC. As example, for E. coli exposed to CST, the regrowth at time 30 h is 2 mg/L during the 1 st TK then increase up to 4 mg/L after 2 nd TK (60 h) with the late regrowth at 8 mg/L (Fig. 1B). Considering now the concentration 4 mg/L, the profile was modified with strong initial decay below the detection limit and late regrowth during 1 st TK, a marked initial decay then a higher regrowth during the 2 nd TK, suggesting a progressive loss of susceptibility to colistin with time. In line with CST results, increased resistance was shown by EC_MCR-1 with PMB as well. The results showed that the maximum regrowth concentration is 1 mg/L in 1 st TK, then increased up to 2 mg/L in 2 nd TK with a late regrowth at 4 mg/L of PMB concentration (Fig. 1D).

Before sequential TK, EC_MCR-1 have shown a low-level of resistance to CST and PMB with respective MICs 2 mg/L for CST and PMB compared to 0.25 mg/L for wild-type strains (Table 2). Then, to check the stability of resistance of strains that regrowth after different polymyxins exposure, MICs to CST and PMB were determined, for each condition where regrowth was observed. The presence of MCR-1 was able to increase polymyxin resistance for E. coli. Indeed, the MICs after 2 nd TK in E. coli carrying MCR-1 (EC_MCR-1_2TK) evaluated at 16 mg/L and 8 mg/L for CST and PMB, respectively (Table 1).

Influence of MCR-1 on expression of genes involved in LPS modification without polymyxins

To determine the initial modification induced by MCR-1 insertion in wild-type strains before contact with polymyxins, a biomolecular analysis of sequence and expression on genes known to be involved in LPS modifications were done. The gene sequences of pmrA, pmrB, phoP, phoQ, mgrB, pmrC and arnT in EC_MCR-1 were compared to its wild-type isogenic strain and no mutation was found (data not shown). However, the expression of regulator genes (pmrA, pmrB, phoP, phoQ) and of effector genes (pmrC, pmrE, lpxM, arnT, cptA, lpxT, and eptB) in EC_MCR-1 were globally up-regulated compared to the wild-type strains before the contact with polymyxin antibiotics (Fig. 2).

Expression of lipopolysaccharide modification genes during polymyxins exposure

Regrowth bacterial population after each TK were harvested to study modifications in sequence and expression of genes involved in polymyxin resistance. For E. coli carrying MCR-1 strains, no modification in gene sequences were found comparing to their initial strains before even after the sequential TK (data not shown). However, the regrowth bacteria exposed to polymyxin antibiotics showed different expression of genes involved in LPS modifications. All genes excepted mcr-1 were down-expressed after the 1 st and 2 nd TK in presence of polymyxins (Fig. 3). Contrary to the findings in wild-type isogenic strains (EC_WT), the average relative expression changes not more than 2-fold, except for the downregulation of phoP gene and high overexpression of lpxM gene (Fig. 3). Overall, the similar genetic expression that shown by EC_WT after consecutive TK is in line with sequential TK results showing the presence of stable heterogenous subpopulations.

DISCUSSION

In the present study, the impact of plasmid-mediated colistin resistance MCR-1 leading to high-level polymyxins resistance has been evaluated during colistin and polymyxin B exposure in isogenic strains of E. coli. As starting point to identify the ability of these bacteria to regrow in presence of polymyxins, time-kill (TK) approach was performed sequentially over wild-type and the MCR-1 transconjugant strains with increasing concentrations of colistin and polymyxin B started from below the MICs to high concentrations (several times the MIC). Indeed, evaluation of resistance by measuring MIC in microdilution is limiting since initial decay and bacterial regrowth is frequently observed during TK experiments leading to detect resistant sub-populations and/or development of adaptative resistance during antibiotic exposure which is known to be a risk factor for the isolation of colistin-resistant subpopulation in Gram-negative bacteria, as it has been shown in MCR-1 transconjugants (1,17,18). Sequential TK in which the regrowth bacteria in the tail of the 1 st time-kill curve were used as an initial inoculum for the next TK is offering a simple approach to discriminate between regrowth due to heterogeneous sub-populations or adaptative resistance as we described recently (16). Then the modification of genes involved in LPS modifications underlying the development of polymyxin resistance were characterized during polymyxins exposure and the influence of the presence of plasmid MCR-1 was evaluated.

Wild-type strains were not able to develop resistance during polymyxins exposure while the presence of MCR-1 lead to polymyxin adaptation

The sequential TK results suggested that wild-type strains were not able to adapt their resistance to polymyxins since no regrowth was observed above the concentration of 0.25 mg/L corresponding to the MICs of CST and PMB as shown in Fig. 1. However, the growth profiles were different between 1 st and 2 nd TK at concentration equal to 0.125 mg/L. During 1 st TK, EC_WT showed fast and similar initial killing and then, start to regrowth in 3 hours after inoculation, whereas during the 2 nd TK the bacteria from 1 st TK exhibited an immediate growth and this dissimilarity suggested the presence of two stable heterogeneous subpopulations with different susceptibilities called "S" (for susceptible) and "R" (for resistant).

Thus the initial decay corresponds to killing of the more susceptible subpopulation and the regrowth corresponds to selection of the resistant subpopulation (16). The resistant subpopulation is generally considered as stable and have to express one or several resistance mechanisms allowing to grow in presence of antibiotic. We observed an overexpression of lpxM gene in E. coli subpopulation (Fig. 3) showing this gene might be responsible for the presence of these "R" phenotype. The lpxM (or msbB) gene encodes the enzyme responsible for the addition of the secondary acyl chains (myristoyl group) to lipid A, which results in the formation of hexa-acylated lipid A (19). An lpxM mutant of E. coli which produce pentaacylated lipid A has been found more sensitive to polymyxins than the wild-type with hexaacylated lipid A (19,20). Moreover, 10 6 to 10 3 log CFU/mL presumably as "R" population in wild-type strains were observed at concentration between 0.25 and 0.5 mg/L of CST and PMB confirmed by PAPs results (Fig. 4) which is consistent with the existence of a heterogenous subpopulation.

Polymyxin antibiotics exhibited rapid and concentration-dependent bacterial killing for EC_MCR-1 during 1 st TK as well as for wild-type strains. Subsequently, sequential TK showed that the presence of MCR-1 was associated with a progressive increase of resistance to colistin and polymyxin B, where a higher concentration of CST and PMB is required to inhibit the growth during the 2 nd TK and suggest continuous adaptation with time. This profile provides a good representative of the unstable homogenous population adaptive resistance (AR) model as describe in our sequential TK study (16). These results in accordance with previous studies showing that the presence of MCR-1 played an important role in increasing MICs values leading to high-level colistin resistance (HLCR) and increased the HLCR mutation rates in E. coli strains (15,22).

An important point associated with the regrowth during TK is to assess the CST and PMB degradation. However, no degradation was measured by LC-MS analysis (data not shown)

for polymyxin antibiotics during sequential TK experiment meaning that the regrowth is only due to increased number of resistant bacteria.

Adaptation of E. coli carrying MCR-1 to polymyxins associated with LPS-modifying genes downregulation

The expression of pmrA, pmrB, phoP, phoQ, pmrC, pmrE, lpxM, arnT, cptA, lpxT, and eptB was over-expressed in EC_MCR-1 compare to their isogenic wild-type (Fig. 2), but they were down-regulated after colistin or polymyxin B exposure (Fig. 3). It is in accordance with previous study showing that most of genes involved in glycerophospholipid metabolism were significantly up-regulated in E. coli carrying MCR-1 compared to the control (wild-type E. coli) under condition of blank media growth, but were down-regulated in presence of polymyxins (22). In the same proteomic and metabolomic studies, mcr-1 gene induced a down-expression of most genes leading to mcr-1-mediated colistin resistance under drug selection pressure then disturbing protein metabolism involved in polymyxin resistance pathway (22). The underlying mechanisms remains unclear since we did not find any mutation in the regulator genes that we have investigated whereas another study have previously shown emergence of some mutations with contact to colistin (15). Therefore, in future work, whole genome sequencing analysis might extend the explanations of which genes have role either in the upregulation of the genes involved in LPS modifications or their down-regulation.

However, it remains unclear to which degree the down-expressed of polymyxin-resistant genes are attributed to high-level polymyxin resistance in E. coli carrying MCR-1. The progressive resistance shown by EC_MCR-1 either might be due partially to the slight increase in relative expression level of mcr-1 genes (1.32-and 1.38-fold after 2 nd TK of CST and PMB, respectively) or might be induce by metabolism alteration by MCR-1 to adapt to polymyxin resistance as similarly described in previous study (15,22). It might be informative for future studies to investigate the structural changes of lipid A to understand the relationship between modification of gene expression and LPS structural modifications that occurs during exposure to polymyxins antibiotics.

MATERIALS AND METHODS

Bacterial strain. Colistin-susceptible Gram-negative bacteria, wild-type Escherichia coli J53 (EC_WT) and its MCR-1 transconjugant strains carrying mcr-1-positive plasmid (EC_MCR-1) were kindly provided by P. Nordmann (University of Fribourg, Switzerland).

Their construction process was described previously (14,23).

MIC determinition. Susceptibility testing of colistin (CST, Lot. SLBG4834V; Sigma-Aldrich, Saint Quentin Fallavier, France) and polymyxin B (PMB, Lot. 016M4099V; Sigma-Aldrich) were performed by microdilution methods in cation-adjusted Mueller-Hinton broth (MHB-CA; Lot. BCBW8159; Sigma-Aldrich) according to joint CLSI -EUCAST protocol (24) and results were interpreted using CA-SFM/EUCAST guideline (25).

Sequential time-kill (TK).

Individual tubes of 15 mL of MHB-CA containing CST and PMB at concentrations ranging from 0.0625 to 1 mg/L for EC_WT and 0.5 to 8 mg/L for EC_MCR-1, were inoculated with the bacterial suspension (~ 1*10 6 CFU/mL) and incubated at 35° ± 2°C, under shaking conditions (150 rpm) up to 30 hours. Bacteria were quantified at 0, 1, 3, 8, 24 and 30 hours by spiral plating on MH agar plates after appropriate serial dilutions (Interscience ® spiral). CFUs were enumerated with an automatic colony counter (Interscience Scan 300) after 24 hours of incubation at 37°C. The theoretical detection limit was to 200 CFU/mL i.e. 2.3 log10 CFU/mL. After the 1 st TK, the regrowth bacteria in the presence of antibiotic were harvested, washed out and then re-inoculated at 10 6 CFU/mL as initial concentration of bacteria to perform the 2 nd TK with CST and PMB concentrations ranging from 0.0625 to 1 mg/L for EC_WT and 1 to 64 mg/L for KP_MCR-1

Population analysis profiles (PAPs).

To decipher heterogeneity of initial bacterial population, PAPs was conducted in three replicates for EC_WT and EC_MCR-1. One hundred µL of bacterial cell suspension (after 24-h cultures) were plated on Mueller-Hinton agar plates containing various concentrations (0, 0.125, 0.25, 0.5, 1, 2, 4, 8, 10, 16 mg/L) of CST and PMB after serial dilutions as described previously (26). CFUs were enumerated as described before.

RT-qPCR. Expression of LPS-modifying genes (pmrA, pmrB, phoP, phoQ, pmrC, pmrE, lpxM, arnT, cptA, lpxT and eptB) and mcr-1 were analysed quantitatively by Two-step Real-Time PCR method. Initially, RNAs of EC_WT and EC_MCR-1, from time 0 and all their regrowth strains from each TKC study, were isolated and purified using a commercially available kit (NucleoSpin ® RNA Plus; MACHEREY-NAGEL; Düren, Germany) following manufacturer recommendations. Then quantity and purity of RNA was determined with a NanoDrop and reverse transcription (RT) was performed starting from 2 µg of isolated RNA using Applied Biosystems™ High-Capacity cDNA Reverse Transkription Kit (ThermoFisher Scientific). cDNA template was diluted one tenth in PCR grade water (Solis BioDyne, Tartu, Estonia). qPCR was done using 5x HOT FIREPol ® EvaGreen ® qPCR supermix (Solis BioDyne, Tartu, Estonia) and the specific primers that was checked using primer BLAST software at NCBI (Table S1). Then, 20 µL of the real-time PCR mixture were analyzed by Applied Biosystems™ 7500 Real-Time PCR Systems (ThermoFisher Scientific). Relative expression of genes was normalized by to the expression of housekeeping genes gapA. The efficiency of amplification and the relative expression were analyzed 2 -∆∆CT method.

PCR amplification and sequencing. Whole cell DNA was extracted by using a commercial kit (NucleoSpin ® DNA RapidLyse; MACHEREY-NAGEL; Düren, Germany) according to the manufacturer protocols. The pmrA, pmrB, phoP, phoQ, mgrB, arnT, and pmrC genes allegedly involved in colistin and polymyxin B resistance were amplified using specific oligonucleotides (Table S1). The amplified DNA fragments were purified by PCR clean-up and gel extraction kit (MACHEREY-NAGEL; Düren, Germany). Genomic DNA of all isolates was visualized and identified using SnapGene software (v3.1.1).

Sequential time-kill to distinguish between polymyxin-induce resistance and heteroresistant in colistin-resistant Acinetobacter baumannii

Hariyanto Ih 1,3 , Nicolas Grégoire E-mail : julien.buyck@univ-poitiers.fr

INTRODUCTION

Acinetobacter baumannii has been reported as one of the most pathogen causing infection problems globally (1) and considered as one of three organisms that clinically responsible for the increasing of the prevalence in both nosocomial and community-acquired infections (2,3). Most of the infections cause by this pathogen occur in critically ill patients in the intensive care unit (ICU) settings with bloodstream infections as the most common clinical manifestations (4,5). Furthermore, A. baumannii has been responsible for almost ventilatorassociated pneumoniae, meningitis, peritonitis, urinary tract infections and wound infections (6,7). The emergence of carbapenem-resistant A. baumannii (CRAB) are on rise with the mortality rates may approach 60% in some parts of the world (8) whereas recent trends exhibit many infections are caused by CRAB or even multidrug-resistant (MDR) A.

baumannii (9). Polymyxins, such as colistin and polymyxin B, are the most reliably effective antimicrobial in vitro against CRAB and MDR A. baumannii isolates (10). Colistimethate sodium or CMS, a prodrug of colistin, is widely used as a current therapeutic option for carbapenem-resistant and MDR A. baumannii infections (11,12) although polymyxin B is a promising alternative since it provide superior in vitro results and less nephrotoxic compare to colistin (13)(14)(15)(16). Currently, with an increase in the use of CMS to treat CRAB infections, colistin resistance is emerging (17,18). The modification of the lipid A of Lipopolysaccharide (LPS) with phosphoethanolamine (PEtN) and loss of LPS are two primary mechanisms that have been described in colistin-resistant A. baumannii to date (19)(20)(21). PEtN addition to the lipid A has been reported responsible to the polymyxin resistance via PEtN transferase PmrC activated by PmrA/PmrB two-component regulatory systems (22,23) and mutations in the three genes involved in the lipid A biosynthesis pathways, namely lpxA, lpxC and lpxD, have been reported responsible for complete loss of LPS (21,24). Colistin-resistant A. baumannii occurred among the patients who had received the CMS treatment over carbapenem-resistant and colistin-susceptible A. baumannii infection (25) but how this strain acquired colistin resistance is poorly understood. Moreover, colistin heteroresistance subpopulation of A. baumannii isolates were particularly found in the patients that previously treated with colistin (21,26). Sequential time-kill (TK) experiments is a simple method to discriminate between a stable heterogenous subpopulations (S/R) and adaptive resistance related to antimicrobial treatments (27). We use this approach in heteroresistance subpopulation selection and predict the adaptive resistance after multiple dosing of colistin and polymyxin B exposure in A. baumannii clinical isolates. In this study, we also characterize the genes involved either in LPS modification or LPS biosynthesis. mg/L of PMB (Fig. 1A). Then 2 nd TK was performed using the regrowth bacteria of 0.5 mg/L of CST and 0.125 mg/L of PMB, as the initial inoculum, and apparently, CST slowly loose its efficacy during the 2 nd TK with the late regrowth can be seen at 2 mg/L of CST on the plate (~3log10 CFU/mL), but no population have been presented in PMB over 0.125 mg/L of PMB concentrations (Fig 1A). MIC determination over these regrowth isolates lead to the similar conclusion whereas the MICCST was gradually increase up to 2 mg/L for ColS_2TK isolate but MIC range are stable at 0.125-0.25 mg/L in PMB (Table 1).

RESULTS

Sequential time-kill with MICs determination

However, different initial MICs value was shown by CST and PMB over ColR, an acquiredresistant isolate after colistin treatment, isolated from the same patients with ColS infections.

MICs of ColR isolates range from 4-8 mg/L and 2 mg/L over CST and PMB, respectively.

As shown in Fig. 1B, the regrowth slightly continues over ~10

Population analysis profiles

PAPs has confirmed the presence of high-level colistin resistant (HLCR) subpopulation in ColR isolates but no resistant subpopulation was found in ColS based on the limit of quantification (LoQ) cutoff point. Figure 2 shows that ColR_Subpopulation grew in the presence of 64 mg/L of CST and PMB. Furthermore, susceptibility assay has confirmed that this subpopulation had MICCST of 128 mg/L but MICPMB 16 mg/L (Table 1).

Genes characterization

Sequencing analysis revealed that pmrA, pmrC, lpxA, lpxC, lpxD gene sequences in both isolates (ColS vs ColR) were identical except the duplication of 30 nucleotides in the pmrB gene "c.48CAGTGTCATCTTAGGTTGTATTTTAATTTT [1]" was found in ColR compare with ColS (Fig. S1). Then, RT-qPCR identified upregulation of the pmrA, pmrB and pmrC (5.34-, 7.91-, and 3.84-fold, respectively) in the resistant isolate ColR compare with that of the isogenic susceptible isolate ColS. In contrast, expression of the lpxM, lpxA, lpxC and lpxD did not differ significantly (Fig. 3).

To explore the difference between the ColR and ColR_Subpopulation, we compared their genes expression level and the data are normalized to the sensitive strains ColS. Genes characterization involved in polymyxin resistance revealed upregulation of pmrA, pmrB and pmrC of 5.34-, 7.91-and 3.84-fold, respectively, in ColR and 5.05-, 6.91-and 3.95-fold, respectively, in ColR_Subpopulation (Fig. 3). In contrast with ColR, lpxM, lpxA and lpxC were up-regulated in ColR_Subpopulation up to 2.45-, 3.90-and 3.68-fold. These results suggest that ColR_Subpopulation provide another resistance mechanism to polymyxins which effectively increased their resistance level.

Next, we investigated the genes expression over the ColS and ColR regrowth isolates from the 1 st and 2 nd TK to explore their expression change under consecutively exposed to high concentration of CST and PMB. The pmrA, pmrB and pmrC gene are significantly downregulated under CST and PMB pressure for all regrowth isolates (Fig. 4). In ColR, lpxM gene was persistently expressed in the limit threshold, but it equally downregulated in ColS.

We observed three genes involved in LPS biosynthesis pathway in ColR, including lpxA, lpxC and lpxD genes. lpxA and lpxD genes expression did not differ compare with T0, but more than 2-fold overexpression was found in lpxC gene with the highest expression shown in CST (Fig. 4). The lpxC gene was up-regulated up to 3.77-and 4.77-fold in CST after 1 st and 2 nd TK, respectively, but only 2.18-and 2.05-fold in PMB after the 1 st and 2 nd TK (Fig. 4).

These results suggest that polymyxin antibiotic selection could affect the LPS modifying genes expression, such as pmrA/pmrB and pmrC genes, and may disturb the biosynthesis of LPS by change the lpxC expression level in vitro. However, we did not find any genes sequences modification in pmrA, pmrB, pmrC, lpxM, lpxA, lpxC and lpxD genes of these all regrowth isolates compare to each their isogenic wild-type.

DISCUSSION

The emergence of colistin-resistant A. baumannii isolates associated with colistin suboptimal dosage during clinical usage

Colistin use is known as a risk factor for the emergence of polymyxin-resistant strains in Gram-negative bacteria and that was associated with the exposure of suboptimal dosage of colistin (28). Therefore, dose of ~9-10.9 million IU/day was administered as the initial daily maintenance of CMS in patients with normal renal functions (creatinine clearance (Clcr) ≥ 90 mL/minute) recommended by international consensus guidelines for the optimal use of the polymyxins, then dose adjustment with renal function monitoring is recommended with the lowest daily dose (patient with Clcr 0 mL/minute) is 3.95 million IU/day to achieve a target average colistin plasma concentration at steady state (Css,avg) of 2 mg/L (16). Here, we used two consecutive MDR A. baumannii clinical isolates from the same patients (with no information about patient renal clearance) that acquired resistance to colistin during treatment (29). After protected specimen brushes confirmed a positive susceptible-colistin A. baumannii isolate (ColS), patient was treated with CMS 3 million IU/day for 8 days, and subsequently, antibiotics were stopped following clinical improvement. Patient became febrile several weeks after, and afterwards, a positive colistin-resistant A. baumannii isolate (ColR) was identified with MICCST >128 mg/L. We found a pmrB mutation in ColR isolate, including duplication of 30 nucleotides in the middle of pmrB gene leading to the pmrA, pmrB and pmrC gene overexpression (Fig. 3 and Fig. S1), which is presumably responsible for its colistin resistance by PEtN addition to lipid A (17). The emergence of colistinresistant clinical isolates of A. baumannii due to failed colistin treatment has been shown

with changes in PmrA and/or PmrB sequences followed by the overexpression of pmrC gene after colistin exposure (17,30). Accordingly, the maintenance dose 3 million IU/day that was administered to the patient with ColS infection would lead to Css,avg lower than 2 mg/L reducing its susceptibility to colistin (31). We speculate that the positive ColR isolate is associated either by bacterial adaption due to colistin suboptimal dosage or the presence of heteroresistant subpopulation since ColS infection was discovered, but no resistant subpopulation has been found in ColS confirmed by PAPs study, as shown in Fig. 2.

Sequential time-kill confirmed the progressive adaptation in ColS and ColR to colistin with time, however no adaptation in ColS and less adaptation in ColR to polymyxin B

In this study, we use sequential TK method where this is a simple approach to discriminate the bacterial regrowth after the antibiotic exposure due to heterogenous sub-populations (S/R) or adaptive resistance (AR) (27). By this approach, we demonstrate that ColS isolate in vitro is able to adapt to CST and potentially develop as resistance isolates. A higher concentration of CST is required to inhibit the growth during 2 nd TK and suggest continuous adaptation with time. This profile provides a good representative of the unstable homogenous population with adaptive resistance as described in our previous sequential TK study (27). The similar profile was shown by ColR isolate under sequential TK of CST where the regrowth bacteria has developed to high level colistin resistance isolate (16-fold MIC) compare to their initial condition (before TK). However, the CST observation that fast triggered antibiotic persistence in vitro and can be followed by the evolution of resistance suggests that resistance may be evolving rapidly in the host as well, as we found in these clinical isolates (32,33).

Our study demonstrated that PMB sulfate in vitro less induce polymyxin resistance rather than CST. Superior in vitro results are seen for PMB compare to CST against two isolates of A. baumannii which agreed with previous polymyxin study (13)(14)(15). This hopefully support the developing research of PMB in clinical using since a large clinical PK/PD include its toxicodynamic study of intravenous PMB is being conducted to optimize the clinical use of PMB (34).

We believe that allowing the activation of stress response is how bacteria respond to antibiotics (35). Without further characterization, the spontaneous resistance (where bacteria may switch back to normal cells after antibiotic treatment) and drug-induced persistence are difficult to distinguish. However, their MICs are unchanged though we perform daily dilution and sub-culturing the culture for 2 months observation (data are not shown) compare with susceptibility data in Table 1.It confirmed no bacteria recovering due to post-antibiotic effect, that reflects phenomena linked to resistance (33).

Overexpression of lpxC gene observed in ColR isolates after sequential TK and two pre-existing population with different polymyxin susceptibility were observed in ColR

An overexpression of lpxC genes and pmrA, pmrB and pmrC downregulation suggested that polymyxin pressure could alterate gene expression level and developed to another resistance mechanism compare to initial strain. A previous multiomics studies where the lpxC mutation caused loss of LPS, showed altered global gene expression, such as RND efflux pump overexpression and down-regulated of FabZ and β-lactamase, leading to high-level colistin resistance (HLCR) in MDR A. baumannii (36). Another previous study have shown that the resistant mutants with the lack of LPS display a HLCR in A. baumannii with MICs of colistin >128 mg/L, and showed a significant decreasing of bacterial fitness compare to the PEtN modification only (37). Fitness cost in A. baumannii is associated with colistin resistant related to growth defect (38). Still, this cannot explain why an initial CFU decay was observed in the resistant mutants during the 2 nd TK (Fig. 1) during selective pressure while the bacterial control in blank liquid media has a stable growth. Contrary found to the previous finding of sequential TK studies in E. coli and K. pneumoniae that shown no initial CFU decay either for (R) subpopulation bacteria or AR mutant (Article 1, 2 and 3). However, when comparing the expression of genes related to LPS modification in this study to those of E. coli studies, it must be pointed out that similar gene regulation was shown, which is exposure of these bacteria to polymyxins could down-regulated LPS-modifying pmrA/pmrB and pmrC gene expression in vitro (Article 3).

Interestingly, a heterogenous subpopulation in ColR isolate was identified which have not been found in the previous study (29). Compare with ColR, ColR_Subpopulation were differently expressed in their lpxM, lpxA and lpxC gene expression (Fig. 3) that may confirm the presence of two different resistant phenotypes in ColR strain. Mutation specifically in lpxA, lpxC and lpxD genes have been inactivated the LPS biosynthesis pathways resulting in the complete loss of LPS and contribute to the occurrence of heteroresistance phenotype of A. baumannii strains (21,24). Heteroresistance subpopulations were particularly found in the patients that previously treated with colistin (26, 39) that may explain the presence of another HLCR subpopulation in ColR isolate. No sequencing data were provided to support this hypothesis, thereby, further work, such as whole genome sequencing and confirmation of LPS production, is certainly required to investigate these initial findings. Despite the limitations that found in this study, our results provide additional information about polymyxin resistance in A. baumannii, and overall, sequential TK may be considered as a promising method to disqualify AR mutant to predict treatments outputs after multiple dosing as used in our previous study. Quentin Fallavier, France) in accordance with joint CLSI -EUCAST as recommended protocol for MIC determination of colistin and results were interpreted according to update EUCAST guidelines and were described as the mean of three replications (40,41).

MATERIALS AND METHODS

Bacterial strain.

Sequential time-kill curve (TKC).

Sequential time-kill curve (sTKC) assay of Acinetobacter baumannii ColS and ColR over colistin (CST) and polymyxin B (PMB) were performed in duplicate by conducting two time-kill (TK) assays consecutively. The survival bacteria that regrew over ~10 7 CFU/mL over 30h in the presence of the highest concentration of antibiotic in the first TKC were harvested by centrifugation then re-suspended to start immediately used for the second TK at an initial inoculum ~10 6 CFU/mL. In the 1 st TK, the antibiotic was added to an overnight culture of ColS or ColR of ~10 6 CFU/mL to yield concentrations ranging from 0.03125 mg/L to 0.5 (for ColS) and from 0.5 mg/L to 16 mg/L (for ColR) then incubated at 37 o C and 150 rpm. Samples were collected at 0; 1; 3; 8; 24 and 30 h after antibiotic addition for colonies counting and after appropriate dilutions with saline, 100 µL samples were spirally plated on Mueller-Hinton agar by using spiral plating (Interscience ® spiral). Colonies were counted with an automatic colony counter (Interscience ® Scan 300) after 24 hours of incubation. The regrowth isolates were harvested and immediately used as initial inoculum for the 2 nd TK with CST and PMB concentration ranging from 0.125 mg/L to 2 mg/L (for ColS) and from 4 mg/L to 256 mg/L (for ColR).

Population analysis profiles (PAPs).

To determine the presence of heteroresistance among the population, PAPs was performed in two replicates for ColS and ColR A. baumannii isolates over colistin and polymyxin B. After 24-h cultures, 100 µL of bacterial cell suspension were platted on Mueller-Hinton agar plates containing gradient of polymyxins concentration (0, 0.125, 0.25, 0.5, 1, 2, 4, 8, 10, 16, 32, 64 mg/L) after serial dilutions, and by use of spiral plating techniques for CFU counting (42). Heteroresistance was considered when polymyxins exhibiting the population growth at or higher than 8-fold MIC (43).

RT-qPCR. Lipopolysaccharide-modifying genes, pmrA, pmrB, pmrC, lpxM, and lipid A biosynthesis genes, lpxA, lpxC, lpxD, were analysed to determine their expression level in ColS and ColR A. baumannii isolates under three different conditions: before contact with antibiotic, after first TKC and after second TKC. RNAs from each isolate were extracted and purified using a commercially available kit (NucleoSpin ® RNA Plus; MACHEREY-NAGEL; Düren, Germany) according to manufacturer recommendations. Reverse transcription (RT) was performed by reacting 2 µg of total RNA in 20 µL reaction of Applied Biosystems™ High-Capacity cDNA Reverse Transkription Kit (ThermoFisher Scientific).

cDNA obtained from RT was diluted one tenth in water PCR grade (Solis BioDyne, Tartu, Estonia) then used as DNA template. qPCR was performed in 20 µL total reaction volume containing cDNA, specific primers and 5x HOT FIREPol ® EvaGreen ® qPCR supermix (Solis BioDyne, Tartu, Estonia). Primers for RT-qPCR were designed using primer BLAST software at NCBI and Primer3 (Table S1). RNAs isolates and water PCR were used as control. Real time PCR mixture were analyzed by Applied Biosystems™ 7500 Real-Time PCR Systems (ThermoFisher Scientific). Relative expression of genes was normalized by to the expression of housekeeping gene 16S RNA as an internal control. The fold changes of gene expression were analyzed by 2 -∆∆CT method. Genes differentially expression were analyzed with the criteria threshold of twofold change (44,45).

PCR amplification and sequencing. Genes sequencing related polymyxin resistance in A.

baumannii, specifically pmrA, pmrB, pmrC (eptA), lpxA, lpxC, lpxD were carried out by sanger sequencing at Service de génétique of Poitiers University Hospital. Whole cell DNA from ColS and ColR A. baumannii isolates under three conditions: before sTKC, after first TKC, and after second TKC, was extracted by using a commercial kit (NucleoSpin ® DNA RapidLyse; MACHEREY-NAGEL; Düren, Germany). All genes were amplified with PCR using specific primers that was checked using primer BLAST software at NCBI as shown in table S1. Amplified PCR product were purified by PCR clean-up and gel extraction kit (MACHEREY-NAGEL; Düren, Germany) then sequenced. Genomic DNA of all isolates was visualized and compared using the molecular biology software SnapGene ® .

DISCUSSION AND PERSPECTIVE

Polymyxins, mainly colistin and polymyxin B, are being used as the last-line therapy option to treat multidrug-resistant Gram-negative bacteria [START_REF] Dhariwal | Colistin: Re-emergence of the "forgotten" antimicrobial agent[END_REF]224). Determining the intrinsic, mutational, adaptive and horizontally acquired mechanisms related to polymyxin resistance are of the main interest that have arisen in the clinic or laboratory. The two-component regulatory systems, PhoP/PhoQ and/or PmrA/PmrB, are the response regulator that known to induce polymyxin resistance in most Gram-negative bacteria by LPS modification that is the main target of polymyxins (16,138). Until it has been reported that polymyxin resistance can be caused by horizontal gene transfer known as plasmid MCR-1, that was firstly reported in two Enterobacteriaceae: Escherichia coli and Klebsiella pneumoniae (20). The primary aim of this study was to describe the molecular impact of chromosomal genes involved in lipopolysaccharide modifications on the selection of polymyxin resistance of two Enterobacteriaceae E. coli and K. pneumoniae carrying plasmid-mediated colistin resistance MCR-1 and two consecutive MDR A. baumannii isogenic isolates (susceptible and resistant to colistin, respectively). We used for our investigation an original approach of sequential time-kill curves.

SEQUENTIAL TIME-KILL

Time-kill is an in vitro study of the effect of static antibiotic concentrations with time. This study allows more precise description of antibacterial effect of an antibiotic on a given bacterial population compared to MIC-based approach. Bacterial regrowth is frequently observed during single time-kill experiments either as a consequence of standard microbroth MIC limitations in detecting small resistant population or a successful adaptation over polymyxins pressure (38,136,222). This single time-kill approach could be coupled linked with previous study that most of genes involved in glycerophospholipid metabolism were significantly up-regulated in E. coli carrying MCR-1 compare to E. coli without carrying MCR-1, but they protein expression were down-regulated in the presence of polymyxins by a proteomic analysis (22). Still, from a same study has also found the role of other mechanisms like overexpression of efflux pump during the presence of polymyxins (22).

In contrast with K. pneumoniae, this strain has not shown the changes of expression related to their LPS-modifying genes in the presence of mcr-1 gene though the measured MICs are not markedly different compare with E. coli. However, its presence mediates selection of high-level polymyxin resistance in K. pneumoniae during colistin and polymyxin B pressure which is higher than E. coli carrying MCR-1 MICs. According to previous studies, they have demonstrated that mcr-1 did not affect the mutation rates of K. pneumoniae (227), and the same level of colistin resistance as we obtained only could be reached by the inactivation of mgrB gene as a negative regulator for PhoP/PhoQ two-component systems (143, 174).

In addition, other studies have shown that the amplified level of polymyxin resistance in the presence of mcr-1 is associated with a significant biological fitness cost in K. pneumoniae (228). Compare to our study, we did not find any characterization assays of chromosomal genes involved in LPS modification over MCR-1-harboring K. pneumoniae strains to date.

Even though we did not replicate the previously reported, our results suggest that the mcr-1 presence can up-regulate the arnT gene that could lead to L-Arabinose addition (16). This modification may confer the level of polymyxins resistance in K. pneumoniae into high-level which is unexplained in the previous studies why the presence of mcr-1 could increase the colistin MICs of K. pneumoniae up to 256-fold change compare with E. coli which is only up to 32-fold change (198).

The activation of two-component systems PmrA/PmrB and PhoP/PhoQ is very depending on the extracellular environmental conditions, such as high ferric (Fe 3+ ) and aluminium (Al 3+ ), low concentration of magnesium (Mg 2+ ) and calcium (Ca 2+ ), or low pH level condition (13,(138)(139)(140)(141). In this study, we used well defined media with fixed ion concentration and neutral pH. Thus, in future work, investigating their expression under variations of pH or ions concentration might prove important. Moreover, in vitro studies have one disadvantage that the situations for bacterial growth and killing are not similar between in vitro and in vivo studies, and therefore, the challenge of extrapolating the obtained in vitro results into in vivo model could be interesting to meet.

Indeed, we carried out the investigation of MCR-1 presence on the well-known genes modifying LPS structure to investigate this resistance mechanism, but our present data lead to the fact that no mutation have been found, particularly in the specific genes target.

Thus, additional mutations on the other genes could be investigated for further studies, like next generation sequencing, since the mutations could be happened in the promotor of these genes target or probably in the other genes. In addition, deleting arnT gene in the MCR-1 K. pneumoniae could investigate the association between the presence of mcr-1 gene and colistin-resistant caused by arnT overexpression.

Ideally, these findings should be confirmed with the structural changes of lipid A as the main component that contribute to polymyxin resistance. Thereby, the understanding of the relationship between modification of gene expression and LPS structural modification might be improved.

Overall, semi-mechanistic PK/PD modelling could help to find the optimal dosing regimen to adapt the treatment of these bacterial infections.

ACINETOBACTER BAUMANNII

The mcr-1 gene has not been observed either in colistin-susceptible or colistin-resistant clinical isolates confirmed by sequencing analysis (data not shown) meaning that the clinical Within this thesis, we highlight three major findings:

1) Sequential TK constitute a simple approach to discriminate different PD model structures. Within this approach, a single bacterial population without adaptation, two stable heterogenous subpopulation (S/R) or unstable homogenous populations with adaptive resistance (AR) models could be characterized to describe the emergence of resistance.

2) Different genes expression profile was observed between two Enterobacteriaceae species, E. coli and K. pneumoniae, in the presence of MCR-1. To our knowledge, this is the first time that MCR-1 plasmid is described to induce different chromosomal LPSmodifying gene regulations depending on the bacterial species and is able to modify the LPS-modification pathway even in the absence of polymyxin.

3) Polymyxin B seems less potent to develop high resistant mutant than colistin. This is the first comparative study between colistin and polymyxin B regarding their potential issue in the emergence of polymyxin resistance over Gram-negative bacteria based on the best of our knowledge. Furthermore, this is the key component in future attempts to overcome the development of polymyxin resistance by considering the use of polymyxin B as alternative to colistin

ACKNOWLEDGEMENTI

  would like to express my deepest appreciation to my advisor Pr William COUET for his continuous support of my PhD program, for your guidance and your constructive criticism. He has been a great mentor in mapping my PhD journey and advising on a research topic. Thanks for giving me an opportunity to join research team INSERM U1070 and working under your supervision.

I

  dedicate this work to all of them… RESUME Caractérisation des mécanismes et modelling PK/PD de la résistance adaptative induite par MCR-1 chez les Enterobacteriaceae Du fait du manque de nouveaux antibiotiques et de l'augmentation des résistances, il est important de comprendre les mécanismes et la dynamique de ces phénomènes. La modification du lipopolysaccharide (LPS) est le principal mécanisme contribuant à la résistance des bactéries aux polymyxines. Le plasmide portant le gène MCR-1 (Mobile Colistin Resistance) retrouvé chez Escherichia coli et Klebsiella pneumoniae code une phosphoethanolamine transférase capable de modifier le LPS par une addition de phosphoethanolamine sur le lipide A du LPS alors que chez Acinetobacter baumannii résistant aux polymyxines il a été décrit à la fois des modifications du LPS par une phosphoethanolamine et une perte du LPS. Cependant, les interactions entre les différents mécanismes exprimés par ces bactéries à Gram-négatif pour devenir résistantes à la colistine et à la polymyxine B sont encore peu décrit. Les courbes de bactéricidies séquentielles ont étés utilisées comme une approche alternative pour discriminer l'héterorésistance de la population bactérienne (2 sous populations S/R) d'une résistance adaptative (AR) durant le traitement par la colistine ou la polymyxine B. Au cours de ce travail de thèse, nous avons : 1. Confirmé que l'approche des courbes de bactéricidies séquentielles peut discriminer trois modèles pharmacocinétique/pharmacodynamique (PK/PD) semimécanistiques décrivant : une population stable héterorésitante (S/R), une population bactérienne sans adaptation et une population bactérienne instable et homogène dont la résistance s'adapte au cours du temps (AR).

3 .

 3 Déterminé les mécanismes impliqués dans la résistance aux polymyxines dans deux souches cliniques d'A. baumannii, isolées avant et après traitement d'un patient à la colistine. Dans ce travail, une nouvelle approche de courbes de bactéricidies séquentielles a été utilisée et validée afin de pouvoir différencier différents modèles PK/PD semi-mécanistiques. De plus, ce travail a montré que la présence du plasmide MCR-1 favorisait l'activation d'autres mécanismes chromosomiques conduisant à de hauts niveaux de résistances aux polymyxines. Enfin, la polymyxine B montrait une plus faible capacité à induire ces mécanismes chromosomiques conduisant à de hauts niveaux de résistance. Mots clés : colistine, polymyxine B, E. coli, K. pneumoniae, A. baumannii, courbe de bactéricidies séquentielles LIST OF COMMUNICATIONS • ORAL presentation at the 30 th European Congress of Clinical Microbiology and Infectious Diseases (ECCMID) | Paris | April 2020 -Sequential time-kill experiments to characterize lipopolysaccharide-modifying genes involved in polymyxin resistance in Escherichia coli and Klebsiella pneumoniae carrying MCR-1 Hariyanto Ih, Nicolas Grégoire, William Couet, Sandrine Marchand and Julien M Buyck. • POSTER presentation at 30th European Congress of Clinical Microbiology and Infectious Diseases (ECCMID) | Paris | April 2020 -Sequential time-kill curve to distinguish polymyxininduced resistance and heteroresistance in Acinetobacter baumannii. Hariyanto Ih, Nicolas Grégoire, William Couet, Sandrine Marchand and Julien M Buyck. • ORAL presentation at 39ème Réunion Interdisciplinaire de Chimiothérapie Anti-Infectieuse (RICAI) | Paris | December 2019 -Rôle de MCR-1 dans la résistance adaptative aux polymyxines. Hariyanto Ih, Nicolas Grégoire, William Couet, Sandrine Marchand and Julien M Buyck. • ORAL presentation at 15th Congrès National de la Société Française de Microbiologie (SFM) | Paris | October 2019 -Genetic characterization of lipopolysaccharide-modifying genes involved in polymyxin resistance in Escherichia coli and Klebsiella pneumoniae carrying MCR-1 by sequential time-kill experiments approach. Hariyanto Ih, Nicolas Grégoire, William Couet and Julien M Buyck • ORAL presentation at 10 th International Seminar of Indonesian Society for Microbiology (10 th ISISM) & 12 th Congress of Indonesian Society for Microbiology (12 th CISM) | Solo, Indonesia | August 2019 -Genetic characterization of lipopolysaccharide-modifying genes involved in polymyxin resistance in Escherichia coli and Klebsiella pneumoniae carrying MCR-1 by sequential time-kill experiments approach. Hariyanto Ih, Nicolas Grégoire, William Couet and Julien M Buyck • POSTER presentation at 29 th European Congress of Clinical Microbiology and Infectious Diseases (ECCMID) | Amsterdam | April 2019 -Sequential time-kill experiments to characterize adaptative resistance to polymyxins in Gram-negative bacteria carrying MCR-1.

Figure 1 .

 1 Figure 1. General schematic of the outer membrane of E. coli K-12 ...............................

Figure 2 .

 2 Figure 2. Detailed structure of Lipid A from Escherichia coli ...........................................

Figure 3 .

 3 Figure 3. Lipid A and Polymyxin B structures and its likely-mode interaction with outer membrane .......................................................................................................................

Figure 4 .

 4 Figure 4. Priority pathogen list identified by WHO ...........................................................

Figure 5 .

 5 Figure 5. Distribution of E. coli isolates fully susceptible and resistance to one or more antimicrobial groups in EU/EEA countries in 2018 ...........................................................

Figure 6 .

 6 Figure 6. Distribution of K. pneumoniae isolates fully susceptible and resistance to one or more antimicrobial groups in EU/EEA countries in 2018 ..................................................

Figure 7 .

 7 Figure 7. Distribution of Acinetobacter species fully susceptible and resistance to one, two and three antimicrobial groups (fluoroquinolones, aminoglycosides and carbapenems) in EU/EEA countries in 2018 ...............................................................................................

Figure 8 .

 8 Figure 8. Lipid A modification by the addition of phosphoethanolamine, aminoarabinose and/or galactosamine that lead to polymyxin resistance ..................................................

Figure 9 .

 9 Figure 9. Regulation pathways of LPS modifications involving PhoP/PhoQ and PmrA/PmrB two-component system ................................................................................

Figure 10 .

 10 Figure 10. Modification of lipid A causing resistance to polymyxin ..................................

Figure 11 .

 11 Figure 11. General features of MCR variants including their phylogenetic relationship with other MCR .......................................................................................................................

Figure 12 .

 12 Figure 12. The prevalence of mobile colistin resistance (mcr) have been identified in various countries .............................................................................................................

Figure 13 .

 13 Figure 13. 2,600-bp-long sequence of the mcr-1 cassette ..............................................

Figure 14 .

 14 Figure 14. Circular maps of four dominant groups plasmids harboring the mcr-1 gene ...

Figure 15 .

 15 Figure 15. Schematic presentation of PK/PD modeling ..................................................

Figure 16 .

 16 Figure 16. Six different PD models to reflect PD models for antibiotics ...........................

  Lipopolysaccharide molecule are divided into three parts, such as O-antigen, core polysaccharides and a hydrophobic component referred to as lipid A.

Figure 1 .

 1 Figure 1. General schematic of the outer membrane of E. coli K-12 (adapted from Ebbensgaard et al., 2018 (48) ).

  part of LPS is core polysaccharide or core-R-antigen which consists of short chain of sugar, including glucose, galactose, heptose and 2-keto-3-deoxyoctonoic acid (KDO). Heptose and KDO are two unusual sugars and are usually present in the core oligosaccharide so it has been used as well as an indicator in LPS assays[START_REF] Sampath | Bacterial endotoxin-lipopolysaccharide; structure, function and its role in immunity in vertebrates and invertebrates[END_REF]. The third part, lipid A, is the lipid part of LPS and bind to core polysaccharide via six position of N-acetyl glucosamine (NAG) of lipid A. Lipid A consists of a phosphorylated NAG dimer with 6 or 7 saturated fatty acid attached. In contrast to the O-antigen, Lipid A structure is highly conserved among GNB[START_REF] Ebbensgaard | The Role of Outer Membrane Proteins and Lipopolysaccharides for the Sensitivity of Escherichia coli to Antimicrobial Peptides[END_REF]. As a major part to stabilize outer membrane structure, lipid A has role as main part of LPS endotoxin activity as well and recognized as a pathogenassociated molecule by immune-cells systems[START_REF] Wang | Lipopolysaccharide: Biosynthetic pathway and structure modification[END_REF].

Figure 2 .

 2 Figure 2. Detailed structure of Lipid A from Escherichia coli (adapted from Steimle et al., 2016 (51) ).

  mode of action involved in their bactericidal activity is the ability to inhibit of bacterial respiration. Based on available evidence, colistin and polymyxin B could inhibit NDH-2, a type II NADH-quinone oxidoreductases. It was suggested that the Nterminal fatty acyl chain and the positive charges of the polymyxin molecule are playing an important role for NDH-2 inhibitory activity(45,[START_REF] Deris | A secondary mode of action of polymyxins against Gram-negative bacteria involves the inhibition of NADH-quinone oxidoreductase activity[END_REF]. NDH-2 in inner membrane of bacteria cells contains a non-covalently bound flavin adenine dinucleotide (FAD) prosthetic group and catalyzes the oxidation of NADH to NAD + coupled to reduction of quinone, which plays a key role in the production of energy (ATP Production) and bacterial respiration[START_REF] Deris | A secondary mode of action of polymyxins against Gram-negative bacteria involves the inhibition of NADH-quinone oxidoreductase activity[END_REF][START_REF] Teh | Type II NADH: Menaquinone Oxidoreductase of Mycobacterium tuberculosis[END_REF].

Figure 3 .

 3 Figure 3. Lipid A and Polymyxin B structures and its likely-mode interaction with outer membrane (adapted from Z. Li & Velkov, 2019 (57) ).

Figure 4 .

 4 Figure 4. Priority pathogen list identified by WHO for new antibiotic research and development (World Health Organization, 2017 (6) ).

Figure 5 .

 5 Figure 5. Distribution of E. coli isolates fully susceptible and resistance to one or more antimicrobial groups in EU/EEA countries in 2018 declared by European Centre for Disease Prevention and Control (ECDC), 2019 (3)

Figure 6 .

 6 Figure 6. Distribution of K. pneumoniae isolates fully susceptible and resistance to one or more antimicrobial groups in EU/EEA countries in 2018 declared by European Centre for Disease Prevention and Control (ECDC), 2019 (3)

Figure 7 .

 7 Figure 7. Distribution of Acinetobacter species fully susceptible and resistance to one, two and three antimicrobial groups (fluoroquinolones, aminoglycosides and carbapenems) in EU/EEA countries in 2018 declared by European Centre for Disease Prevention and Control (ECDC), 2019 (3)

  . LPS can be extensively modified by the addition of 4-amino-4-deoxy-L-Arabinose (L-Ara4N) and LITERATURE REVIEW Polymyxin Resistance in Gram-Negative Bacteria phosphoethanolamine (PEtN), thus reducing the negative charge of lipid A and in consequence the binding of polymyxins (49, 136). Generally, the addition of L-Ara4N is preferentially added at the 4' phosphate position and PEtN is added to the 1-phosphate of lipid A, but in some cases, either one or two L-Ara4N and/or PEtN could modified 4' phosphate and 1-phosphate. The addition of Galactosamine (GalN) in 1-phosphate, a compound is structurally similar to L-Ara4N, can modify the LPS structure as well and decrease the negative charge on the lipid A that recently was found in clinical isolates of A. baumannii (137).

Figure 8 .

 8 Figure 8. Lipid A modification by the addition of phosphoethanolamine, aminoarabinose and/or galactosamine that lead to polymyxin resistance (adapted from Pelletier et al., 2013 (137) ).

  Francisella tularensis encoded by two genes, flmK and flmF2 (162). The flmK gene has been identified as an orthologue of E. coli arnT and the flmF2 is an orthologue of E. coli arnC where those involved in the substitution of L-Ara4N to lipid A in polymyxin-resistant E. coli strains (162).

Figure 10 .

 10 Figure 10. Modification of lipid A causing resistance to polymyxin (adapted from Dortet et al., 2016) (163) ).

Figure 11 .

 11 Figure 11. General features of MCR variants including their phylogenetic relationship with other MCR (Adapted from Khedher et al., 2020 (207) ).

Figure 12 .

 12 Figure 12. The prevalence of mobile colistin resistance (mcr) have been identified in various countries (Adapted from Elbediwi et al., 2019 (209) ).

Figure 11 Figure 13 .

 1113 Figure 11 with the start codon of mcr-1 was identified at position 79 and a promotor region,

Figure 14 .

 14 Figure 14. Circular maps of four dominant groups plasmids harboring the mcr-1 gene

  bloodstream and UTIs recovered, meaning that these isolates are less pathogen(213). A very recent study has a same conclusion shown that the prevalence of mcr-1 positive E. coli have been increased over the year, though the number has remained low among clinical patients in China with contributed relatively small to patient mortality (215). Mortality rates in mcr-1-positive E. coli infection was not differ with mcr-1-negative groups, suggesting that mcr-1-positive E. coli infection does not substantially affect to patient outcomes (215).Overall, health-care contact was the most probable risk factor for mcr-1-positive E. coli infection (215).No historical data related colistin and polymyxin B used in the previous three months or during the patient treatment due to mcr-1-positive E. coli infection in these both studies, thereby the clinical impact of mcr-1 on the selection of highlevel polymyxin resistance isolates associated with polymyxin exposure is hard to concludeMost of mcr-1-positive E. coli clinical isolates (96%) showed resistance to colistin with MICs 4-16 mg/L, and the remaining (4%) were susceptible (215). In addition, most of mcr-1 positive E. coli isolates are resistant to ciprofloxacin, cefotaxime and cefepime (213).

Figure 15 .

 15 Figure 15. Schematic presentation of PK/PD modeling as combination of pharmacokinetic and pharmacodynamics (adapted from Derendorf & Meibohm, 1999 (218)) Related to the bacterial resistance issue, PK/PD modeling has been proven useful in the

Figure 16 .

 16 Figure 16. Six different PD models to reflect PD models for antibiotics.A susceptible bacterial population without adaptive resistance(1) or with the capacity to

ARTICLE 2 -Modélisation pharmacodynamique des courbes de bactéricidies séquentielles présentant une resistance adaptative du MCR- 1

 21 Sequential time-kill study of K. pneumoniae with colistin 102 Klebsiella pneumoniae a la colistine avec surexpression du gène arnT On considère généralement que les souches bactériennes porteuses du gène MCR-1 de résistance à la colistine mobile (mcr) présentent une résistance de faible niveau, mais que la résistance adaptative peut alors se développer rapidement. Des courbes de bactéricidie séquentielles (TK) ont été menées pour étudier la résistance adaptative à la colistine (CST) d'une souche transconjugante de Klebsiella pneumoniae portant le plasmide MCR-1 (KP_MCR-1), en utilisant la souche de type sauvage (KP_WT) pour comparaison. L'expression et les mutations des gènes impliqués dans la résistance à la CST ont été étudiées. KP_WT à la CST a été caractérisée par une CMI égale à 0,25 mg / L stable avec le temps. KP_MCR-1 était initialement moins sensible, avec une CMI à 2 mg / L, mais une résistance adaptative s'est rapidement développée avec des CMI estimées à 16 et 64 mg / L à la fin du premier et de la deuxième TK, respectivement. D'un point de vue mécanistique, le résultat le plus spectaculaire était une surexpression d'environ 20 fois du gène arnT pendant l'exposition au CST dans KP_MCR-1 mais pas dans KP_WT, aucune mutation n'a été trouvée dans les gènes de modification du LPS. D'un point de vue pharmacodynamique (PD), une CMI instantanée dérivée d'un modèle (MICinstant) a été proposée pour mieux caractériser la résistance adaptative rapide à la CST dans KP_MCR-1. En conclusion, cette étude a montré que la présence du gène mcr-1 induit une diminution relativement modeste de la sensibilité initiale à la CST chez K. pneumoniae, mais qu'elle est également responsable d'une résistance adaptative prononcée conduisant à une résistance élevée à la CST. La CMI de la CST contre que la CMI de KP_MCR-1 estimée avant le début du traitement surestime considérablement l'efficacité réelle de la CST après plusieurs jours de traitement, ce qui peut induire une sélection posologique inappropriée et un échec des traitements.

  conditions (TK) should now be confirmed in dynamic conditions (hollow-fibers experiments) and over a longer duration in order to tentatively predict what could happen after several days of treatment, as it is the case in clinical practice. However, MICinstant provides practical quantification of the rapid adaptive resistance to CST developed by KP_MCR-1 but not KP_WT, with potentially important consequences in clinics. In the case of KP_WT, CST antimicrobial activity does not seem to vary with time and therefore the initial MIC value determined experimentally constitutes a valid tool for dosing regimen selection. By contrast the estimated MIC of CST against KP_MCR-1 represents an initial antimicrobial activity that should dramatically overestimates the real CST efficacy after several days of treatment. This may induce inappropriate dosing selection and treatments failure.

FIG 1 FIG 2 FIG 3 FIG 4

 1234 FIG 1 Sequential time-kill (TK) results of colistin (CST) against 2 isogenic isolates. (Top)

)

  Where multiple functions for KCST (h-1) were tested: a linear function( 𝐾 𝐶𝑆𝑇 = 𝑘 𝑠𝑙𝑜𝑝𝑒 × [𝐶𝑆𝑇]), a power function (𝐾 𝐶𝑆𝑇 = 𝑘 𝑠𝑙𝑜𝑝𝑒 × [𝐶𝑆𝑇] 𝛾 ), an Emax function (𝐾 𝐶𝑆𝑇 = 𝐸𝑚𝑎𝑥×[𝐶𝑆𝑇] 𝐸𝐶 50 +[𝐶𝑆𝑇] ) or a sigmoidal Emax function (𝐾 𝐶𝑆𝑇 = 𝐸𝑚𝑎𝑥×[𝐶𝑆𝑇] 𝛾 𝐸𝐶 50 𝛾 +[𝐶𝑆𝑇] 𝛾 ). Models including 1 and 2 subpopulations with different antibiotic susceptibilities (i.e. different estimated values for EC50) were tested to characterize the emergence of resistance. Adaptive resistance sub-model A model including a single homogenous bacterial population with adaptive resistance to CST was tested as an alternative to the previous model with distinct bacterial populations, to model the emergence of resistance. Compartments ARon and ARoff representing the fraction of adapted and non-adapted bacteria respectively were added in the model and KCST was reduced proportionally to ARon. 𝑛 -𝐾 𝐶𝑆𝑇 (1 -𝐴𝑅𝑜𝑛) × 𝐵 𝑛 (Equation 6) At the beginning of the experiment all bacetria are assumed to be non-adapted (ARon = 0 and ARoff = 1). Multiple functions for Kon (h -1 ) were tested: a linear function (𝐾𝑜𝑛 = 𝐾𝑜𝑛 𝑠𝑙𝑜𝑝𝑒 × [𝐶𝑆𝑇]), a power function (𝐾𝑜𝑛 = 𝐾𝑜𝑛 𝑠𝑙𝑜𝑝𝑒 × [𝐶𝑆𝑇] 𝛿 ), an Emax function (𝐾𝑜𝑛 = 𝐾𝑜𝑛 𝑚𝑎𝑥 ×[𝐶𝑆𝑇] 𝐾𝑜𝑛 50 +[𝐶𝑆𝑇] ) or a sigmoidal Emax function (𝐾𝑜𝑛 = 𝐾𝑜𝑛 𝑚𝑎𝑥 ×[𝐶𝑆𝑇] 𝛿 𝐾𝑜𝑛 50 𝛿 +[𝐶𝑆𝑇] 𝛿 ). Caractérisation des gènes modifiant les lipopolysaccharides impliqués dans la résistance aux polymyxines chez Escherichia coli porteur de MCR-1 par approche les courbes de bactéricidies séquentielles Les résistances aux polymyxines, antibiotiques de dernier recours, sont en augmentation. Il a été précédemment rapporté que le plasmide MCR-1 codant pour une phosphoéthanolamine transférase conduisait à une résistance de bas niveau. Cette étude a examiné le rôle du MCR-1 dans la résistance adaptative à la polymyxine d'E. coli apar une approche sde courbes de bactéricidies séquentielles. Les courbes de bactéricidies (TK) ont été menées contre E. coli de type sauvage (EC_WT) et son transconjugant portant le plasmide MCR-1 (EC_MCR-1) avec des concentrations en série de colistine et de polymyxine B. En parallèle, l'expression et les mutations de gènes impliqués dans la résistance aux polymyxines ont été étudiées. Les TK séquentielles ont illustré la présence de deux populations hétérogènes stables dans EC_WT par rapport à une seule population avec une résistance adaptative dans EC_MCR-1. La résistance a augmenté progressivement jusqu'à 8 fois à la CST et 4 fois à la PMB pour EC_MCR-1 après ladeuxième TK (60 h). L'étude de l'expression des gènes impliqués dans la modification des lipopolysaccharides pour EC_MCR-1 a montré une augmentation avant le contact avec les antibiotiques puis une diminution après les TK séquentielles. Les souches de type sauvage n'ont pas montré de résistance adaptative aux polymyxines tandis que la présence de MCR-1 suggère une adaptation continue avec le temps. Ces résultats suggèrent que le plasmide MCR-1 favorise la sélection d'un autre mécanisme de résistance conduisant à développer une résistance de haut niveau aux polymyxines.

  « Pharmacologie des anti-infectieux », UFR de Médecine Pharmacie, Université de Poitiers, Poitiers, France 2 Laboratoire de Toxicologie-Pharmacocinétique, CHU de Poitiers, Poitiers, France 3 Universitas Tanjungpura, Pharmacy Department, Faculty of Medicine, Pontianak, Indonesia *Corresponding author: Dr. Julien M. Buyck Mailing adresse : INSERM U1070, PBS, Bâtiment B36, Secteur α, Niveau 2, 1 Rue Georges Bonnet, TSA 51106, 8073, Poitiers Cedex 9. Phone : +33-(0)5-49-45-43-79 Fax : +33 (0)5-49-45-43-78 E-mail : julien.buyck@univ-poitiers.fr INTRODUCTION Lipopolysaccharides is the most contributing component to polymyxin resistance where it can be extensively modified by the addition of either 4-amino-4-deoxy-L-arabinose (L-Ara4N) in the 4'-phosphate or phosphoethanolamine (PEtN) in 1-phosphate of lipid A, thus reducing the negative charge of lipid A and consequently, the binding of polymyxins (1, 2).

FIG 1 FIG 2

 12 FIG 1 Sequential time-kill (TK) of colistin (CST) and polymyxin B (PMB) against wild-

FIG 3 FIG 4

 34 FIG 3 Genes relative expression of wild-type E. coli (EC_WT) and its MCR-1

  Phone : +33-(0)5-49-45-43-79 Fax : +33 (0)5-49-45-43-78

  Two consecutive MDR A. baumannii isolated from the same patient, a colistin-susceptible A. baumannii (ColS) and colistin-resistant A. baumannii (ColR) isolate, were used in this study. Colistin (CST) and polymyxin B (PMB) exhibit different time-killing profile against ColS during sequential TK without different initial MICs value between these two antibiotics (0.125 mg/L). PMB shown a better bactericide activity compare to CST where no bacterial population are shown from 3 hours since the 1 st TK was initiated at the presence of 0.25

FIG 1 (TABLE 1 aFIG 2

 112 FIG 1 (A) Sequential time-kill (TK) of colistin-susceptible A. baumannii (ColS) over

FIG 3

 3 FIG 3 Relative expression of pmrA, pmrB, pmrC, lpxM, lpxA, lpxC and lpxD genes considering the colistin-resistant A. baumannii (ColR) clinical isolates and its high-level colistin resistant subpopulation (ColR_Subpopulation) isolated from 64 mg/L of colistin MH agar in PAPs compared to the colistin-susceptible clinical isolates (ColS). Limit threshold foldchange is indicated by grey area. Values are presented as mean and error bars represented SD for three biological replicates.

FIG 4

 4 FIG 4 Relative expression of pmrA, pmrB, pmrC, lpxM, lpxA, lpxC and lpxD genes as the colistin-susceptible (ColS) and colistin-resistant (ColR) of A. baumannii isolates after consecutively 1 st and 2 nd TK experiments over colistin (CST) and polymyxin B (PMB), compared and normalized to their initial isolates before contact with antibiotics. Limit threshold foldchange is indicated by grey area. Data are presented as mean and error bars represented SD for three biological replicates.

  resistance was not cause by the presence of this gene. Our in vitro sequential TK results also confirmed the emergence of colistin-resistant A. baumannii clinical isolates in the patient with colistin-susceptible A. baumannii infection was associated with the suboptimal dosage of colistin treatment (229). The exposure of suboptimal dosage colistin may facilitated the selection of moderate-level colistin-resistant mutant and reduce the susceptibility to colistin (38, 132), which is not shown in polymyxin B based on our in vitro results. We confirmed the presence of two different phenotype with a very large MICs difference in colistin-resistant isolates. During sequential TK observation, we noticed that continuing colistin treatment over colistin-resistant A. baumannii (colistin MICs 4-8 mg/L) isolates has the risk to facilitate the emergence of high-level colistin resistance mutants in A. baumannii (colistin MICs ≥128 mg/L after sequential TK), which explain why colistinresistant A. baumannii with colistin MICs ≥128 mg/L was observed after patient received 8 days colistin treatment (229). Nevertheless, in line with our Enterobacteriaceae studies, no progressive continuous adaptation shown by both A. baumannii clinical isolates over polymyxin B during our sequential TK observation. Even though not linked, our results ties well with previous three clinical A. baumannii study that demonstrated the concentrationvs-time profiles of polymyxin B rapidly attained target concentration and greater-extensive bacterial killing than that seen with colistin dosage regimen (230). It still remains unclear the role of mcr genes in the emergence of colistin-resistant A. baumannii clinical isolates for which resistance to colistin is still limited to chromosomeencoded resistance, such as pmrCAB operon and lpxCAD (231, 232). To date, only a study has been detected a mcr-1 positive A. baumannii clinical isolate with no different MICs compare with a mcr-1 negative clinical strains showing there is no clinical consequences associated mcr-1 gene presence over this strain (233). The presence of a novel plasmidencoded mcr-4.3 gene was lately identified in a colistin-resistant A. baumannii clinical strain and its presence was associated with colistin resistance (234). For that reason, we excluded the investigation of the relationship between A. baumannii and MCR-1 mediated polymyxin resistance in this study.

  and Julien M Buyck. 2019.

	LIST OF ABBREVIATIONS EUCAST : European Committee on Antimicrobial Susceptibility Testing
	ExPEC	:	Extraintestinal pathogenic E. coli
	AMR	:	Antimicrobial resistance
	ATP	:	Adenosine triphosphate
	AUC	:	Area under the curve
	CA-SFM	:	Comité de l'Antibiogramme -Société Française de Microbiologie
	CFU	:	Colony-forming unit
	cKp	:	Classical Klebsiella pneumoniae
	BLA	:	Beta-lactamase
	Clcr	:	Creatinine clearance
	CLSI	:	Clinical and Laboratory Standards Institute
	CMS	:	Colistin methanesulphonate/ colistimethate sodium
	CoQ1	:	Coenzyme-Q1 or Ubiquinone-1
	CPS	:	Capsule polysaccharide
	Css,avg	:	Average drug concentration at steady state
	Dab	:	Diaminobutyric acid
	D-Leu	:	D-leucine
	D-Phe	:	D-phenylalanine
	ECDC	:	European Centre for Disease Prevention and Control
	ECVs	:	Epidemiological cutoff values
	EHEC	:	Enterohemorrhagic Escherichia coli
	EPEC	:	Enteropathogenic Escherichia coli
	ETEC	:	Enterotoxigenic Escherichia coli
	E-test	:	Epsilometer test
	EU/EEA	:	European Union/ European Economic Area

Table 1 .

 1 The chemical structures of polymyxin B and colistin (polymyxin E) ..................

Table 2 .

 2 Antibacterial spectrum of colistin and polymyxin B ............................................

Table 3 .

 3 Polymyxin breakpoints according to the CLSI and EUCAST guidelines ............

Table 4 .

 4 Estimation of hvKp proportion among K. pneumoniae infections .......................

Table 5 .

 5 Lipopolysaccharides remodeling employed by Gram-negative bacteria ............

Table 1 .

 1 The

	Polymyxin	Fatty acyl group	Pos. 6	Pos. 7
	Polymyxin B B1	(S)-6-methyloctanoyl	D-Phe	Leu
		B1 -Ile	(S)-6-methyloctanoyl	D-Phe	Ile
		B2	6-methylheptanoyl	D-Phe	Leu
		B3	Octanoyl	D-Phe	Leu
		B4	Heptanoyl	D-Phe	Leu
		B5	Nonanoyl	D-Phe	Leu
		B6	3-hydroxy-6-methyloctanoyl	D-Phe	Leu
	Colistin/	E1	(S)-6-methyloctanoyl	D-Leu	Leu
	polymyxin E	E1 -Ile	(S)-6-methyloctanoyl	D-Leu	Ile
		E1 -Val	(S)-6-methyloctanoyl	D-Leu	Val
		E1 -Nva	(S)-6-methyloctanoyl	D-Leu	Nva
		E2	6-methylheptanoyl	D-Leu	Leu
		E2 -Ile	6-methylheptanoyl	D-Leu	Ile
		E2 -Val	6-methylheptanoyl	D-Leu	Val
		E3	Octanoyl	D-Leu	Leu
		E4	Heptanoyl	D-Leu	Leu
		E7	7-methyloctanoyl	D-Leu	Leu
		E8 -Ile	7-methylnonanoyl	D-Leu	Ile
	Pos.: Amino acid position

chemical structures of polymyxin B and colistin (polymyxin E) (adapted from Velkov et al., 2013 (14) ).

LITERATURE REVIEW

Polymyxins: The arising of "old" class antibiotics

Table 2 .

 2 Antibacterial spectrum of colistin and polymyxin B (adapted fromLi et al., 2019 (12) ).

	Enterobacteria-	Non-fermentative	Others	Mycobacterium
	ceae	GNB
	Susceptible E. coli,	Acinetobacter	Haemophilus	M. xenopi
	K. pneumoniae,	baumannii,	spp.,	M. intracellulare M. tuberculosis
	Citrobacter spp.,	Pseudomonas	Bordetella	M. fortuitum
	Enterobacter spp.,	aeruginosa,	pertussis,	M. phlei M. smegmatis
	Salmonella spp.,	Stenotrophomonas	Legionella
	Shigella spp.	maltophilia	spp.,
			Aeromonas
			species
			(except Ae.
			Jandaei)
		Burkholderia cepacia
		complex,
		P. pseudomallei,
		Moraxella catarrhalis,

Resistant

Proteus spp., Providentia spp., Serratia spp., Brucella spp. Gram-positive bacteria, Vibrio spp., Morganella morganii, Helicobacter pylori, Neisseria spp.

(meningococci and gonococci), Edwardsiella tarda.

LITERATURE REVIEW

Polymyxins: The arising of "old"

class antibiotics 3. ANTIMICROBIAL SUSCEPTIBILITY TESTING OF POLYMYXINS

	Several studies have been published related to MIC distribution of colistin and polymyxin B
	against E. coli, K. pneumoniae, A. baumannii and P. aeruginosa by variety of method,
	including Etest ® and agar dilution (60-62). Later, MIC determination for colistin and
	polymyxin B by disk diffusion methods was not recommended after a comparative study
	showing that disk diffusion testing methods failed to reliably detect polymyxin-resistant

strains in clinical isolates of Acinetobacter spp, Pseudomonas aeruginosa, and Enterobacteriaceae

[START_REF] Tan | Comparison of three standardized disc susceptibility testing methods for colistin[END_REF][START_REF]Recommendations for MIC determination of colistin (polymyxin E) As recommended by the joint CLSI -EUCAST Polymyxin Breakpoints Working Group[END_REF]

. Indeed, polymyxins as a polypeptide antibiotics have a difficulty to diffuse in agar resulting in small zones of inhibition

[START_REF] Tan | Comparison of three standardized disc susceptibility testing methods for colistin[END_REF]

. Although, a variety of studies exhibited a good result for the gradient diffusion test, such as E-test method

(65- 67)

, several studies revealed that this method failed to detect the resistance to the polymyxins of clinical carbapenem-resistant isolates of A. baumannii and Enterobacteriaceae

[START_REF] Ezadi | Antimicrobial Susceptibility Testing for Polymyxins: Challenges, Issues, and Recommendations[END_REF]

. Likely with agar diffusion, this problem might be due to the polymyxin difficulty to diffuse in agar.

A

joint working group was established by Clinical and Laboratory Standards Institute (CLSI) and European Committee on Antimicrobial Susceptibility Testing (EUCAST) to recommend the most appropriate MIC determination regarding

	3.1. CLINICAL BREAKPOINTS
	If a standard reference method has already been established, there is no consensus
	between these two professional organizations related to colistin and polymyxin B
	breakpoints. Before 2019, only P. aeruginosa and A. baumannii colistin and polymyxin B
	MIC breakpoints with no interpretive criteria for Enterobacteriaceae were provided by CLSI,
	which is only epidemiological cutoff values (ECVs) were used as clinical breakpoints. After
	a pharmacokinetic/ pharmacodynamic (PK/PD) review, outcomes and MIC distribution data,
	breakpoints for colistin and polymyxin B are available for Enterobacteriaceae, P. aeruginosa
	and A. baumannii but no interpretative criteria for polymyxin B in EUCAST guideline (69,
	70). But based on breakpoints recommendations of la Société Française de Microbiologie
	(French Microbiology Society), interpretative criteria for polymyxin B were available based
	on colistin data (71). Only intermediate and resistant without susceptible category was
	suggested in CLSI guideline regarding to the limited clinical efficacy of colistin and
	polymyxin B even for isolates with MIC values <2 mg/L based on the clinical and PK/PD
	recommendation (further detail will be explained in "clinical use" part).

by several methodological issues of in vitro susceptibility testing in polymyxins. The issues have been comprehensively investigated and it was agreed that ISO-Standard broth microdilution method (20776-1) is the best reference testing for Enterobacteriaceae, Acinetobacter spp., and Pseudomonas aeruginosa

[START_REF]Recommendations for MIC determination of colistin (polymyxin E) As recommended by the joint CLSI -EUCAST Polymyxin Breakpoints Working Group[END_REF]

.

Table 3 .

 3 Polymyxin breakpoints according to the CLSI and EUCAST

guidelines Microorganisms Polymyxin CLSI 1 CA-SFM/ EUCAST 2 MIC breakpoint (mg/L) 3 MIC breakpoint (mg/L) 3

			S	I	R	S	I	R
	Enterobacteriaceae	Polymyxin B	-	≤2	≥4	≤2	-	>2
		Colistin	-	≤2	≥4	≤2	-	>2
	Acinetobacter spp.	Polymyxin B	-	≤2	≥4	≤2	-	>2
		Colistin	-	≤2	≥4	≤2	-	>2
	Pseudomonas spp.	Polymyxin B	-	≤2	≥4	≤2	-	>2
		Colistin	-	≤2	≥4	≤2	-	>2
	Clinical and Laboratory Standards Institute, 2019 (69)
	Société Française de Microbiologie and European Committee on Antimicrobial Susceptibility Testing, 2020 (71)
	S, susceptible; I, intermediate; R, resistant; -, not determined

LITERATURE REVIEW Polymyxins: The arising of "old" class antibiotics 4. CLINICAL USE 4.1. COLISTIN

	A. COMMERCIAL PREPARATION
	At first introduction into clinical practice, colistin was commercially offered as a greater or
	equal antibacterial potency compared to polymyxin B but less toxic as its sulphomethylated
	derivative, sodium colistin methanesulphonate (CMS, colistimethate sodium, sodium
	• Sulphate salts of polymyxins must be used since an inactive prodrug of
	colistimethate, penta-sodium colistimethanesulphate, sulphomethyl colistin) (58). A
	methanesulfonate derivative of colistin breaks down slowly in solution.

common problem of polypeptide compounds is an induction of site painful irritation during subcutaneous or intramuscular injection that could be overcomed by sulphomethylated derivatives, which

	firstly introduced by Stansly and his co-worker in
	1947. Sulphomethylation of colistin was firstly applied by Koyama in 1957 and still
	administered intravenously in the clinic until now (12, 72). Commercially, colistin is available
	in two forms, colistin sulphate (hereafter referred to as colistin) and colistin
	methanesulfonate (CMS).

Polymyxin B is commercially available as polymyxin B sulphate and not indicated for

	(Kwa et al., 2007). Polymyxin B is not prepared as a prodrug. In clinical use, polymyxin B
	sulphate can be used as intramuscular, intravenous, inhalation, intrathecal and topical
	routes preparations (58).
	B. CLINICAL PRACTICE
	Like colistin, polymyxin B is available to treat infections cause by MDR and XDR Gram-
	negative bacteria by intravenous administration as the most often use in clinical (77).
	Intramuscular route is rarely used since it may cause local pain and not appropriate in
	polymyxin B nowadays. This antimicrobial is less active against lung infection but preferable
	used in invasive infections for routine systemic use regarding it shown an excellent PK
	profile compare to colistin with lower risk to cause nephrotoxicity (27). As a background,
	pharmacokinetic/ pharmacodynamic/ toxicodynamic (PK/PD/TD) of polymyxin B has never
	oral use and likewise. No sulphomethylated derivative of polymyxin B is available in clinical
	use. Like we explained in the previous chapter, sulphomethylated derivative of polymyxins
	are required to reduce the pain of injection site cause by lipopeptide agents. In 1961, the
	sodium salt of sulphomethylated derivative of polymyxin B has been used intramuscularly
	and intraventricularly in 5 patients with P. aeruginosa secondary meningitis infection. It was
	found as well that no toxicity observed, and all five patients cured (76). However, this
	derivative has never been applied into clinical practice until present for unknown reason

Among Enterobacteriaceae isolates, E. coli remains the second most common strains producing carbapenemase (31.5%) behind K. pneumoniae (38.5%) (

	In France, an epidemiological studies of carbapenemase-producing E. coli shown that most
	carbapenem resistant strains were found in urine samples (67.9%), followed by blood, bile
	and wound samples at 7.5%, 7.5% and 5.6%, respectively (88). Among the 140 studied
	isolates collected from Paris and suburbs, the Northeast of France and the southeast of
	France, 74.3% of isolates produced an OXA-48-like carbapenemase which are categorized
	. Based on their infection site, pathogenic E. coli are determined into two group, as susceptible to imipenem according to EUCAST breakpoints but still controversial for in
	namely enteric or intestinal pathogenic E. coli that may cause diarroghenic syndrome or vivo results (88). The other isolates produced class B metallo-β-lactamases, NDM-type
	other intestinal disease, and extraintestinal pathogenic E. coli (ExPEC) as a causes of (20.7%) and VIM-type (3.6), and KPC-3 carbapenemase (0.7%). Fifty different sequence
	extraintestinal disease, such as urinary tract infection (UTI), haemolytic uremic syndrome types (STs) have been identified from the total isolates showing a large diversity of these
	(HUS) and meningitis (82-85). carbapenemase-producing E. coli isolates (88). However, all isolates susceptible to colistin
	(100%) and only 95% and 96% of the isolates are susceptible to Fosfomycin and
	A. EPIDEMIOLOGY OF E. COLI INFECTIONS
	nitrofurantoin, respectively (88). Among carbapenemase-producing E. coli cases, OXA-48-
	E. coli is one of Gram-negative bacteria that might cause nosocomial infections. They cause producing K. pneumoniae was found, suggesting an in vivo transfer in patient's gut and
	12-50% of hospital-acquired infections and associated with 4% cases of diarrheagenic support the previous findings that dissemination across diversified species among
	syndrome. In United States, E. coli is the primary cause of both community-acquired acquired and nosocomial urinary tract infection (UTI) with up to 50% prevalence mostly in female because of the urinary tract anatomical structure difference with male (85, 86), while Enterobacteriaceae is possible (88). 88).
	in tropical countries, EPEC is the leading cause of childhood diarrhea (86). ETEC is the
	B. ANTIMICROBIAL RESISTANCE IN E. COLI
	most common pathogen that cause traveler's diarrhea for the visitors in several developing
	countries (86). Neonatal meningitis-causing E. coli cause 8% mortality rate and most of the Broad spectrum antimicrobial agents are recommended and often used to treat community-
	survivors have developed neurological complications and septicemia associated with E. coli and hospital-acquired infections cause by E. coli, such as β-lactams (particularly third
	has similar mortality and morbidity rate same as with aerobic Gram-negative bacilli (86). In generation cephalosporins), fluoroquinolones, aminoglycosides and trimethoprim-
	Europe, E. coli outbreaks were mostly caused by EHEC (87). STEAEC strains were sulfamethoxazole, although nitrofurantoin and fosfomycin are used in several countries
	reported mostly in Central Europe and responsible for Germany outbreak during 2011 with
	more than 900 of HUS. Urinary tract infections caused by MDR UPEC strains have been
	Increased in Europe, with the most prevalence cases are Spain and Italy (87).

Table 4 .

 4 Estimation of hvKp

	Country	Time frame	Isolate source/characteristic	No./total (%)
				of hvKp
				infections

a proportion among K. pneumoniae infections (Adapted from Russo & Marr, 2019 (107) ).

  Fe 3+ ), aluminium (Al 3+ ), the presence of cationic peptide, or low pH level condition (e.g., pH 5.5) was necessary and its location in periplasmic can phosphorylate the regulatory of PmrA protein. PhoQ histidine kinase is activated as a low concentration of Mg 2+ or Ca 2+ response, cationic peptide and low pH (e.g., pH 5.5) then activates the response regulator PhoP by phosphorylation, which can further activate PmrA/B regulator via pmrD over-transcription leading to up-regulate various of LPS-modifying genes, such as pmrCAB (also called eptA) operon and arnBCADTEF (also called pmrHFIJKLM or pmrF or arnT) operons, and promote the addition of PEtN and L-Ara4N, respectively(13, 140, 141). Normally, the expression of mgrB gene represses the PhoQ and PmrB protein sensor kinase contains 2 transmembrane regions, a domain in cytoplasmic and periplasmic domain. As a study found in S. enterica, The PhoQ and PmrB periplasmic domain are directly responding the extracellular Mg 2+ and Fe 3+ , respectively.There are 2 high affinity Mg 2+ transporters, mgtA and mgtCB, which transcription is controlled by PhoPQ regulatory system (144). These 2 transporters will be overexpressed in low Mg 2+ condition, followed by PhoP expression, and as consequent, the expression of other 40 protein is modulated by PhoP, including LPS-modyfing genes (144). In contrast, no other regulation pathways related to PmrB during high Fe 3+ (145). Iron directly bind to the periplasmic domain of PmrB, then phosphorylate PmrA then modified LPS to protect bacteria from toxicity. Metal ions, such as Fe 3+ and Al 3+ , bind the negatively-charged surface

	). Two-component
	regulatory systems are signal transduction machineries by using reversible phosphorylation
	between two proteins, a sensor kinase and a response regulator, to mediate the adaptation

of changing environmental conditions (138, 139). PmrB protein is required for iron sensing so the activation in extracellular if high ferric (expression of PhoQ-encoding gene leading to negative regulation of the PhoP/PhoQ twocomponent system (142). But the inactivation of this gene may cause the overexpression of the PhoP/PhoQ two-component system as commonly found in K. pneumoniae strains, thus causing LPS modifications (143). Figure 9. Regulation pathways of LPS modifications involving PhoP/PhoQ and PmrA/PmrB two-component system (adapted from Ezadi et al., 2019 (68) )

of GNB resulting in bacteria cell death as like polymyxin effect (145). Thus, PmrAB regulates the surface modifications to decrease iron binding to the bacterial cell, so the bacteria are able to grow in the presence of toxic level.

In many cases, the presence of antimicrobial peptides, including polymyxins, could directly stimuli PhoQ respond through a highly acidic surface of the PhoQ sensor domain, increased PhoP phosphorylation and bring a resistant phenotype (146, 147). However, P. aeruginosa PhoQ has not able to sense the presence of antimicrobial peptide, and rather sensed by other TCSs ParRS and CprRS (148, 149). Moreover in P. aeruginosa, not only PhoPQ, but PmrAB system also directly responds to low Mg 2+ condition but not high level Fe 3+ condition (147). In A. baumannii, PmrB is required for low pH-induced polymyxin resistance and not induced by high levels of Fe 3+ (150).

aeruginosa is dependent on the expression of arnBCADTEF single operon. Polymyxin resistance in A. baumannii due to L-Ara4N addition have not been identified until present

  concentration to modify their LPS(151, 152). This activation could be induced in response to low Mg 2+ and the presence of antimicrobial peptide, such as

colistin and polymyxin B (147, 151). Moreover, in another study, PhoQ Mutations that inactivate PhoQ sensor kinase lead to increased PhoP activity were found in P. aeruginosa and increased L-Ara4N addition to lipid A (141). It was found that the mutation of PmrB sensor kinase can promotes L-Ara4N addition as well and increased resistance to polymyxin (147).

The addition of L-Ara4N in K. pneumoniae, E. coli and P.

A study in Salmonella enterica has found that the LPS modification by L-Ara4N addition also can modify by the activation of pmrE (or Ugd) gene which activates by the phosphorylated PmrA from PmrA/B TCSs (153). Not only PmrA, it has been identified that pmrE gene can additionally phosphorylated by another gene, namely etK (153). Regarding polymyxin resistance, the LPS modification by L-Ara4N addition confers a higher level of resistance than PEtN modifications only which increased the resistance up to 250-fold in the mutant expressing L-Ara4N in the lipid A only (154, 155). Thus, in LPS modification, the arnT operon play an important role in high-level polymyxin resistance than pmrC and cptE which only mediated PEtN addition. LITERATURE REVIEW Polymyxin Resistance in Gram-Negative Bacteria B. ADDITION OF PHOSPHOETHANOLAMINE (PEtN) PEtN expression firstly has been identified in S. enterica that encodes by PmrC (also known as EptA or PagB) via PmrA/B TCS activation. In

contrast with L-Ara4N that plays a greater role in polymyxin resistance, the PEtN substitution to lipid A via pmrC gene inactivation only provide the polymyxin resistance up to 5-fold than the wild-type strain showing the low-level polymyxin resistance

  (156). But similarly by L-Ara4N, the addition of PEtN in either 4' position or 1 position of lipid A is possible in the absence of L-Ara4N (137). In A. baumannii, PEtN addition to the lipid A has been reported responsible to

the polymyxin resistance via PEtN transferase PmrC activated by PmrA/PmrB TCSs (157, 158). It was found in A. baumannii mutants with substitution in pmrAB genes that colistin resistance was increased of between 4-and 128-fold due to PEtN substitution of the lipid A without showing any high ferric (Fe 3+ ) level dependent (150, 157, 158).

The emergence of colistin-resistant clinical isolates of A. baumannii due to failed colistin treatment has been shown with changes in PmrA and/or PmrB sequences followed by the overexpression of pmrC after colistin exposure (159). Fitness cost of A. baumannii were correlated with these mutations showed reduced in vitro growth and in vivo growth in animal model without decreasing the level of disease in mice (160).

Moreover, the roles of PhoP/PhoQ roles related to polymyxin resistance in A. baumannii isolates have not been identified, though these two proteins play important roles in the PEtN and L-Ara4N substitution of lipid A. Additionally, not only by pmrCAB operon, the phosphorylated heptose residue as LPS core can be further modified by PEtN regulated by cptA gene which is activated by phosphorylated PmrA as found in S. enterica

(16, 155)

.

C. ADDITION OF GALACTOSAMINE (GalN)

Galactosamine is a

novel structure modifying LPS that has been identified in colistin- resistant of A. baumannii isolates

  (137). This compound has found as a second amino sugar that present on the terminal phosphate residues of lipid A alongside with PEtN in resistant strains of A. baumannii from patients treated with colistin. These modifications have been determined as a colistin-induce lipid A modifications since no modification were identified before colistin treatments by MALDI-TOF MS (137). The expression of NaxD deacetylase, a protein encoded by naxD gene, was identified as a mediator of this

modification, and it was demonstrated that naxD gene is regulated by PmrA/PmrB regulatory system (161). However, lipid A modification by GalN has similarly found in

LOSS OF LIPOPOLYSACCHARIDE Loss of lipopolysaccharide (LPS) is one of the remodeling LPS mechanisms that currently has only been found in A. baumannii.

  Another regulator, namely CrrA/CrrB (colistin resistance regulation) operon which encodes two protein, CrrA regulator protein and CrrB sensor kinase, have been identified as well to play an important role in polymyxin resistance though its physiological role remains unknown(13). The CrrAB genes was particularly found in K. pneumoniae genomes but not in E. coli (164). However, a study explained that inactivation of CrrB gene may cause the activation of arnBCADTEF operon, pmrC and pmrE genes via pmrAB overexpression, and as a consequent, the expression of L-Ara4N and PEtN (164). Mutation in CrrB protein Mutations, including substitution or deletion of nucleotides, in the three genes involved in the lipid A biosynthesis pathways,

LITERATURE REVIEW

Polymyxin Resistance in Gram-Negative Bacteria D. OTHER REGULATORY SYSTEM by six amino substitution have been reported as being responsible for its inactivation (164, 165).

Another two-component regulator associated polymyxin-adaptive resistance, ParR/ParS, was described in P. aeruginosa (148). This system was required to upregulate the expression of arnBCADTEF operon in the presence of sub-MICs polymyxins leading to resistance to colistin and polymyxin B (148). These arn genes participates in the LPS modification by 4-aminoarabinose (L-Ara4N) addition to lipid A, but different with PhoP/PhoQ, it is not required for ParR/ParS to activate arn operon under Mg 2+ -limiting conditions where peptide sensor ParS might induced by certain peptides (148). Moreover, different with PmrA/PmrB, expression of ParR/ParS is not under the control of PhoP/PhoQ as well described in P. aeruginosa (148). Others TCS that contribute to the regulation of polymyxin resistance in P. aeruginosa have been identified as well, such as cationic peptide resistance (CprR/CprS) and ColR/ColS (166, 167). Similar with ParRS regulator, the CprRS regulated the addition of L-Ara4N to lipid A by activate the arn/pmr operon in response to specific antimicrobial peptide via CprS sensor kinase, such as polymyxin, indolicidin and pleuricidin, but did not affect the response to low Mg 2+ and/or High Fe 3+ (166). In contrast, ColRS has been shown to increase of the PEtN transferase by activate pmrC (EptA) and decrease L-Ara4N via arnT gene in response to Zn 2+ presence (167).

1.2.

namely lpxA, lpxC and lpxD, have been reported that is responsible for this mechanism

(18, 19)

. Two insertional of insertion sequence (IS) elements, such as ISAba11 and IS4-family elements, in the three lipid A biosynthesis genes have been inactivated the biosynthesis pathways resulting in the complete loss of LPS and contribute to the occurrence of heteroresistance phenotype of A. baumannii strains

(18, 19)

. Mutations specifically in lpxC and lpxD genes have been reported involved in A. baumannii resistant to polymyxin B and the mutation in lpsB gene (encoding glycosyltransferase for LPS core biosynthesis) has been identified for the lack of LPS production (168, 169). The resistant mutants with the lack of LPS display a high-level colistin resistance in A. baumannii with > 128 mg/L of colistin MICs, and moreover, this loss of LPS showed a significant decreasing of bacterial fitness compare to the PEtN modification caused by pmrAB mutations only (160). It is poorly understood how A. baumannii is able to survive in the LPS deficiency condition. However, LPS-deficient lpxA mutants shown the overexpression of proteins involved lipoprotein and phospholipid transport and the production of the surface polysaccharide acetylglucosamine that possibly important for A. baumannii survival during the absence of LPS (170).

Table 5 .

 5 Lipopolysaccharides remodeling employed by Gram-negative bacteria to achieve polymyxin resistance

	Resistance mechanisms	Genes	Bacteria	References
		involved
	Activation of LPS-	pmrA/pmrB	E. coli, K.	(139, 141, 147,
	modifying genes by two-	and/or	pneumoniae, P.	158, 171-173)
	component systems	phoP/phoQ	aeruginosa, A.
			baumannii and S.
			enterica
	Inactivation of phoP/phoQ	mgrB	K. pneumoniae	(143, 174)
	negative feedback
	regulator
	Lipid A modification by	pmrC, cptA	E. coli, K.	(140, 156, 157)
	phosphoethanolamine		pneumoniae, A.
	(PEtN) addition		baumannii and S.
			enterica
	Lipid A modification with	arnBCADTEF	S. enterica, E. coli, K.	(153, 175-177)
	Aminoarabinose (L-	operon and	pneumoniae, P.
	Ara4N) addition	pmrE	aeruginosa.
	Increased acylation of	lpxM	S. enterica, E. coli, K.	(178, 179)
	Lipid A enhancing its		pneumoniae,
	modification with
	aminoarabinose
	Modification of lipid A with	cptA	S. enterica	(155)
	PEtN
	Decrease the negative	lpxT	S. enterica	(180)
	charge of lipid A by inhibit
	its phosphorylation
	Modification of KDO (3-	eptB	E. coli	(181)
	deoxy-D-manno-
	octulosonic acid) with
	PEtN
	Loss of lipopolysaccharide	lpxA, lpxC, lpxD	A. baumannii	(18, 19)

LITERATURE REVIEW

Polymyxin Resistance in Gram-Negative Bacteria

1.3. CAPSULE FORMATION

The capsule polysaccharide (CPS) has been shown in Klebsiella 70 neumonias and

  . In P. aeruginosa, PhoP/PhoQ systems regulates the OprH outer membrane porin that is encoded by the first gene of oprH of the phoPQ operon (187). The loss of expression of oprH, phoP and phoQ by the inactivation of PhoP reduced polymyxin B resistance in P. aeruginosa (187). The mutation of OmpU porin in Vibrio cholerae increased the susceptibility to polymyxin B through the mechanism that

currently unclear (188). Mutation of porB genes also increase polymyxin susceptibility in Neisseria meningitidis but it is still unclear whether PorB work alone or together with Mtr efflux to confers this resistance since transposon insertion in three genes mtrC, mtrD and mtrE that critical for MtrCDE efflux pups were found (189).

LITERATURE REVIEW Polymyxin Resistance in Gram-Negative Bacteria plates

  in a population analysis profile study, heteroresistance of A. baumannii clinical isolates have been shown up to 128-fold MIC colistin increased compare to susceptible populations(196). In polymyxin B experiments, heteroresistant Enterobacteriaceae showed an increase of MICs up to 32 mg/L without showing any reversibility to being susceptible after 20 days of passages defined these resistant phenotypes are stable(12).

  2, was firstly reported inBelgium. It shares 76.75% nucleotide identity with mcr-1 and it is nine bases shorter than mcr-1 (200). The 1,626-bp-long sequences of mcr-3 has been widely characterized in E. coli and mainly identified in Asia, Europe and North America and shared 45% and 47% nucleotide sequence identity to mcr-1 and mcr-2, respectively, but interestingly shared 99.8-100% amino acid sequence to PEtN transferases found in Enterobacteriaceae (201).The mcr-4 (1,626 bp) and mcr-5 (1,644 bp) genes were first identified in salmonella and E. coli from European countries and subsequently further detected in Enterobacter cloacae and E. coli from Singapore and Japan(202, 203). The mcr-4 encoded large amino acid Salmonella enterica serotype Typhimurium and may confer colistin resistance after cloned into colistin susceptible E. coli NEB5α (199). The amino acid sequences of mcr-9 are highly similar at the structural level with those of mcr-3, mcr-4 and mcr-7 based on lipooligosaccharide phosphoethanolamine transferase EptA (199).

	sequences with 34%, 35% and 46% identity to PEtN transferases of MCR-1, MCR-2 and
	MCR-3, respectively (203), while MCR-5 is distinct with protein identities of 36.11%,
	35.29%, 34.72% and 33.71% to MCR-1, MCR-2, MCR-3 and MCR-4, respectively (202).

Two another mcr homologues, mcr-6 (was firstly identified as mcr-2.2) and mcr-7, were found deposited into genbank with 1,617 bp and 1,620 long sequences, respectively. The mcr-6 gene found in Moraxella pluranimalium shared 87.9% amino acid sequences of PEtN transferases identity to MCR-2 but had only colistin MIC of 1-2 mg/l (204). The MCR-7 (defined as MCR-7.1) protein that was detected in K. pneumoniae isolated from chicken in China is distinct with amino acid identities of 35%, 34%, 70%, 45%, 36% and 33% from MCR-1, MCR-2, MCR-3, MCR-4, MCR-5 AND MCR-6 (205).

In contrast, mcr-8 gene that was characterized in 2018 in K. pneumoniae isolated from pneumoniae sputum of ICU patients in China shares only 31.08%, 30.26%, 39.96%, 37.85%, 33.51%, 30.43%, and 37.46% nucleotide identity to mcr-1, mcr-2, mcr-3, mcr-4, mcr-5, mcr-6 and mcr-7 (206).

Although eight mcr homologues (mcr-1 to -8) mostly have been identified in Enterobacteriaceae, the latest novel mcr homologue, namely mcr-9, was recently reported in a LITERATURE REVIEW Polymyxin Resistance in Gram-Negative Bacteria

  with different drug concentrations cannot be determined from the MIC approach, since both killing pattern can converge to the same MIC value over this time period. Last, because only free drug concentration was considered in MIC test, it is needed to consider protein binding when extrapolate in vitro results to human studies.

Third, with only 24-h time point measurement, bactericidal or LITERATURE REVIEW PK/PD of Antibiotics bacteriostatic effect

Les courbes de bactéricidies séquentielles, une astuce expérimentale simple pour distinguer deux modèles pharmacocinétique/pharmacodynamique présentant deux sous populations hétérogènes distinctes ou une population homogène avec résistance adaptative

  K g , rate constant for multiplication of bacteria; E max , maximum kill rate constant; E max(0) , maximum kill rate constant when no adaptive resistance has developed; EC 50 , PMB concentration producing 50% of E max(0) ; EC 50,S and EC 50,R , PMB concentration producing 50% of E max for (S) and (R) bacteria, respectively; μ, sigmoidicity factor; AR off and AR on , compartments describing adaptive resistance being off and on, respectively; K on , rate constant for development of adaptive resistance.

	Des expériences ont été menées avec la polymyxine B et deux souches isogéniques de
	Klebsiella pneumonia (le type sauvage, KP_WT, et son transconjugant portant le gène
	mobile de résistance à la colistine, KP_MCR-1) pour démontrer que la réalisation de deux
	expériences consécutives des courbes de bactéricidies (TK séquentielles) représente une
	approche simple pour discriminer	différents modèles pharmacocinétiques/
	pharmacodynamiques avec deux sous-populations hétérogènes ou avec une seule
	population présentant une résistance adaptative.

genes related to LPS modification or LPS biosynthesis over two consecutive MDR A. baumannii, ColS and ColR, isolated from the same patient. ColS was isolated before colistin treatment, and ColR is a strain acquired resistance to colistin during the treatment.

ARTICLE 1 -Sequential Time-kill study to discriminate PK/PD Model FIG 1 Schematic illustrations of the S/R model (A) and AR model (B). C PMB , PMB concentration; S, compartment with PMB-sensitive bacteria; R, compartment with resistant bacteria; B, compartment with homogenous bacterial population;

TABLE 1

 1 Statistical comparison of various parameters for S/R and AR models

Model results [estimate and relative standard error b (%)] for strain:

		KP_WT				KP_MCR-1
		1 TK		Sequential TK		1 TK		Sequential TK
	Parameter a	S/R	AR	S/R	AR	S/R	AR	S/R	AR
	BIC	23.4	39.5	35.1	208.8	14.1	47.1	163.7	86.5
	INOC (log10 CFU/ml) 5.60 (2.1)	5.52 (2.5)	5.63 (2.0)	5.55 (4.1)	5.78 (1.8)	5.9 (2.5)	5.64 (2.9)	5.56 (2.2)
	INOC 2 (log 10 CFU/ml)			5.93 (0.9)	5.03 (3.2)			5.3 (2.6)	5.85 (1.9)
	B max (log 10 CFU/ml)	9.29 (1.2)	9.32 (1.1)	9.24 (1.3)	9.19 (2.0)	9.34 (1.6)	9.24 (1.4)	9.1 (1.6)	9.13 (1.0)
	mutf (log 10 CFU/ml)	-3.69 (9.0)		-3.49 (10.4)		-4.46 (8.9)		-10.5 (7.8)
	K g (h -1 )	1.54 (8.1)	1.15 (15.2)	1.42 (10.4)	0.935 (20.1)	(S), 1.03 (12.8); (R),	0.959 (15.9)	(S), 1.64 (20.0); (R),	1.58 (7.9)
						0.568 (8.0) c		1.19 (8.4) c
	E max (h -1 ) E max(0) (h -1 )	4.40 (5.9)	5.18 (8.2)	4.36 (4.8)	4.92 (13.7)	3.24 (6.4)	5.28 (10.8)	5.41 (10.3)	7.43 (7.0)
	EC 50 (mg/liter)		0.121 (5.7)		0.371 (14.3)		1.85 (23.3)		6.98 (14.6)
	EC 50,S (mg/liter)	0.0631 (2.2)		0.065 (15.6)		0.932 (7.2)		1.87 (31.0)
	EC 50,R (mg/liter)	0.141 (1.3)		0.162 (4.5)		3.9 (13.8)		31.1 (18.1)
	μ	10 (fixed) d	2.39 (15.1)	5.01 (15.3)	3.33 (33.4) 3.8 (18.7)	1 (fixed) e	1 (fixed) e	1 (fixed) e
	K on (h -1 )		0.0956 (17.5) f		0.001 (1.2) f		0.0856 (17.2) f		0.0547 (7.5) g
	K on50 (mg/liter)								2.89 (7.4)
	6								3.63 (9.8)
	o (log 10 CFU/ml)	0.255 (19.3) 0.382 (20.4)	0.29 (10.7)	1.97 (14.9) 0.226 (17.0)	0.498 (18.1)	0.825 (13.3)	0.469 (8.4)

a INOC, bacterial count at time 0 (before the start of the 1st TK); INOC2, bacterial count at 30 h (before the start of the 2nd TK); Bmax, maximum bacterial population size supported by the system; mutf, fraction of resistant bacteria (R) at time 0; Kg, apparent growth rate constant; Emax, maximum kill rate constant; Emax(0), maximum kill rate constant when no adaptive resistance has developed; EC50, PMB concentration that produces 50% of Emax(0); EC50,S and EC50,R, PMB concentrations that produce 50% of Emax for the (S) and (R) subpopulations, respectively; μ, Hill coefficient in PMB effect relationship; Kon, rate constant for development of adaptive resistance to PMB; Kon50, PMB concentration yielding 50% of Kon; 6, Hill coefficient for rate constant for development of AR; o, additive residual error on log10 scale for total bacteria count. b Relative standard error obtained by sampling importance resampling. c

  cus aureus. Antimicrob Agents Chemother 50:2957-2965. https://doi .org/10.1128/AAC.00736-05. 11. Tsuji BT, Bulitta JB, Brown T, Forrest A, Kelchlin PA, Holden PN, Peloquin CA, Skerlos L, Hanna D. 2012. Pharmacodynamics of early, high-dose linezolid against vancomycin-resistant enterococci with elevated MICs and pre-existing genetic mutations. J Antimicrob Chemother 67: 2182-2190. https://doi.org/10.1093/jac/dks201. 12. Landersdorfer CB, Rees VE, Yadav R, Rogers KE, Kim TH, Bergen PJ, Cheah S-E, Boyce JD, Peleg AY, Oliver A, Shin BS, Nation RL, Bulitta JB. 2018. Optimization of a meropenem-tobramycin combination dosage regi-men against hypermutable and nonhypermutable Pseudomonas aeruginosa via mechanism-based modeling and the hollow-fiber infection model. Antimicrob Agents Chemother 62:e02055-17. https://doi.org/10 .1128/AAC.02055-17. 13. Bulitta JB, Yang JC, Yohonn L, Ly NS, Brown SV, D'Hondt RE, Jusko WJ,

	Forrest A, Tsuji BT. 2010. Attenuation of colistin bactericidal activity by
	high inoculum of Pseudomonas aeruginosa characterized by a
	new mechanism-based population pharmacodynamic model. Antimicrob
	Agents Chemother 54:2051-2062. https://doi.org/10.1128/AAC
	.00881-09.

TABLE 1

 1 Susceptibility data of colistin against wild-type K. pneumoniae (KP_WT) and K.

	pneumoniae carrying MCR-1 (KP_MCR-1) isolates, before (0 h) and after sequential time-kill
	(TK) a
	Strain	MIC (mg/L)
	KP_WT	0.25
	KP_WT_1TK	0.25
	KP_WT_2TK	0.25
	KP_MCR-1	2
	KP_MCR-1_1TK	16
	KP_MCR-1_2TK	64

a 1TK and 2TK indicate that the surviving bacteria were isolated from the tail of survival curve from first TK (30 h) and second TK (60 h), respectively.

TABLE 2

 2 Parameter estimates for the PD model based on KP_WT and KP_MCR-1 sequential time-kill kinetics in the presence of CST

	Parameter	Description	Estimate (RSE%) KP_WT KP_MCR-1
	Bmax (log10 cfu/mL)	Maximum bacterial population size supported by the system	9.23 (0.7)	9.22 (1.3)
	Kg (h -1 )	Apparent growth rate constant	1.14 (4.1)	1.16 (16.6)
	β (h -1 )	Rate constant characterizing the delay in the growth of bacteria	0.338 (15.2) 0.276 (60.5)
	Emax (h -1 )	Maximum kill rate constant	3.09 (7.7)	-
	Emax(0) (h -1 )	Maximum kill rate constant when no adaptive resistance has developed	-	10.5 (16.5)
	EC50 (mg/L)	Drug concentration that produces 50% of Emax for KP_WT or 50% of Emax(0) for KP_MCR-1	0.162 (7.8) 13.7 (19.6)
	γ	Hill coefficient in drug effect relationship	4.76 (31.7)	1 (fixed)
	Konmax (h -1 )	Maximum rate constant for development of adaptive resistance to antibiotic	-	0.067 (19.9)
	Kon50 (mg/L) Drug concentration yielding 50% of Kon	-	2.69 (44.2)
	σ (log10 cfu/mL)	Additive residual error on log10 scale for total bacteria count	0.248 (21.7) 0.352 (10)
	RSE (Relative Standard Error)

TABLE 1

 1

	Susceptibility data of colistin (CST) and polymyxin B (PMB) against wild type E. coli
	(EC_WT) and E. coli carrying MCR-1 (EC_MCR-1), before (0 h) and after sequential time-kill curve
	(TK) a
	Strain	MICCST (mg/L)	MICPMB (mg/L)
	EC_WT	0.25	0.25
	EC_WT_1TK	0.25	0.25
	EC_WT_2TK	0.25	0.25
	EC_MCR-1	2	2
	EC_MCR-1_1TK	8	4
	EC_MCR-1_2TK	16	8
	a 1TK and 2TK indicate that the surviving bacteria were isolated from the tail of TKC in first TK (30 h) and
	second TK (60 h), respectively.

TABLE S1

 S1 Primer used in this study

	Utilisation	phoQ -R	CTGCAACCGATTATAACGGATGCT
		mgrB -F mgrB -R	GTTAGGCGCTGTTTAACTAACGCA CGCTATTCTACCACTGCTGGAGA	This study
	Strain E. coli J53	Primer arnT -F1 RT-qPCR arnT -R1 arnT -F2	Sequence (5' to 3') ATATTGCCGGACGTGAAGGC CAGAACGGAGCTCTATGTTGGG CAACGCTTTGCACTGGATGATG	Reference This study
		gapA F arnT -R2 gapA R pmrC -F1	CGACAAATATGCTGGCCAGG CGCTAAGCAAGCTGGCAAAG GTAGTAGCGTGAACGGTGGT GGCTTAATTTTGCTTTGCGAGCAT	(1)
		pmrA -F pmrA -R pmrC -R1 pmrC -F2	TTGCAGGGACTGATTCTGGC ACCAGGCTGTAATGACCTGC GCGGTATTAGGGAAATAGACCACG CCGCGCTGAATCTACCTGAT	(2) This study
		pmrB -F pmrB -R pmrC -R2	CCATCGGGGCCATTTTGTTG AGGCTGACCATAAAGACGCC CGCCAGAATCAGTCCCTGCAATAA	This study
		PhoP -F PhoP -R	TGTCGATCTCGGATTGCCAG GGGAGCGAAATGACCTGTGA	This study
		PhoQ -F PhoQ -R	AAACGTCTACCCGGCAACAT CTGGATTGAGCAATTCGCGG	This study
		pmrC -F pmrC -R	CCGCGCTGAATCTACCTGAT GAGGCGGATAGCGGTTGTAA	This study
		pmrE -F pmrE -R	TTACCGTCACGCGTTGCTAT GGTTGGAGTGGCGATGATGA	This study
		lpxM -F lpxM -R	TTCCGTGATCCCATTCTGGC TCTGGAAAGCAGAGCGACAG	This study
		arnT -F arnT -R	CGGCCTCTTCGCGTTTATTG CAGATGGGGCACAATCCAGT	This study
		cptA -F cptA -R	GGTTGGGCACTGCTCTACTT AACAGAACGCTCTGCGAGAA	This study
		lpxT -F lpxT -R	TCATGGATTCTGGTTGCCGA CATCGCCAGCAGTGAACAAC	This study
		eptB -F eptB -R	TTTCTGCGTTGGGGCTGTAT GCAGTGAGAGTTTGGTTGCG	This study
		Sequencing
		pmrA -F pmrA -R	TACCAGGCTGCGGATGATATTCT TAGTTTTCCTCATTCGCGACCAG	This study
		pmrB -F pmrB -R	CGCGGCTTTGGCTATATGCTG TTAACTACCGTGTTCAGCGTGC	This study
		phoP -F phoP -R	CCCCCATAACCACATAATCGCG TTGCCAACAGAAAACGTACCCG	This study
		phoQ -F	CCAAGAAGTGATTACCACCGTTCG	This study

des courbes de bactéricidies séquentielles pour distinguer la résistance induite par la polymyxine et l'hétérorésistance chez Acinetobacter baumannii aux polymyxines

  pmrB (8 fois) et pmrC (3,9 fois). Les PAPs ont confirmé la présence d'une souspopulation résistante avec une expression génétique différente dans ColR mais pas dans ColS. Aucune autre mutation n'a été trouvée dans ColS et ColR après le 2ème TK.

	La résistance aux polymyxines est de plus en plus fréquemment rapportée. Dans cette
	étude, une méthode de courbes de bactéricidies séquentielles (TK séquentielles) a été
	utilisée pour décrire la résistance adaptative à la colistine (CST) et à la polymyxine B (PMB)
	de deux isolats cliniques d'A. Baumannii, un colistin-sensible (ColS) et un colistin-résistant
	après traitement à la colistine (ColR). Les modifications des gènes impliqués dans la
	résistance aux polymyxines ont été caractérisées par séquençage et RT-qPCR. Les TK
	séquentielles ont été réalisées en utilisant CST et PMB à une concentration de 0,25x à 64x
	MIC. En parallèle, l'hétérorésistance a été quantifiée par des profils d'analyse de population
	(PAP). Parallèlement, les bactéries ont été analysées par séquençage et RT-qPCR pour
	déterminer le changement des gènes impliqués dans les modifications des
	lipopolysaccharides (LPS) (pmrA, pmrB, pmrC, lpxM) et la biosynthèse des LPS (lpxA, lpxC,
	lpxD). Les repousses de bactéries de la souche ColR ont éyté observées jusqu'à 16 fois la
	CMI pour la CST après le 2ème TK mais seulement jusqu'à 4 fois la CMIpour la PMB. Avant
	Cependant, une surexpression significative de lpxC a été montrée pour ColR après la 2ème
	TK, uniquement avec la CST (5 fois) mais pas avec la PMB. Nous avons également montré
	que la résistance de haut niveau à la CST de la souche ColR était vraisemblablement
	causée par une perte de production de LPS.

le contact avec les polymyxines, les séquences des gènes de pmrA, pmrC, lpxM, lpxA, lpxC et lpxD pour les deux isolats étaient identiques à l'exception de pmrB qui montraient l'ajout de 10 acides aminés. La souche ColR présentait égalementune surexpression de pmrA (5 fois),

  1,2 , Sandrine Marchand 1,2 , William Couet 1,2 , Julien M.

	Buyck 1 *
	1 INSERM U1070 « Pharmacologie des anti-infectieux », UFR de Médecine Pharmacie,
	Université de Poitiers, Poitiers, France
	2 Laboratoire de Toxicologie-Pharmacocinétique, CHU de Poitiers, Poitiers, France
	3 Universitas Tanjungpura, Pharmacy Department, Faculty of Medicine, Pontianak,
	Indonesia
	*Corresponding author: Dr. Julien M. Buyck
	Mailing adresse : INSERM U1070, PBS, Bâtiment B36, Secteur α, Niveau 2, 1 Rue Georges
	Bonnet, TSA 51106, 8073, Poitiers Cedex 9.

  Two clinical carbapenem-resistant A. baumannii isolates, colistinsusceptible A. baumannii (ColS) and colistin-resistant A. baumannii (ColR), were kindly provided by T. Naas from Institut Pasteur, Université Paris-Sud, Paris, France. Two consecutive MDR A. baumannii were isolated from the same patient wherein ColS was isolated before colistin treatment and ColR, strain acquired resistance to colistin during the treatment, was isolated after antibiotics were stopped (29).

	Antibiotic susceptibility testing. MICs determination of colistin (CST, Lot. SLBG4834V;
	Sigma-Aldrich, Saint Quentin Fallavier, France) and polymyxin B (PMB, Lot. 016M4099V;

Sigma-Aldrich, Saint Quentin Fallavier, France) were determined by microdilution methods in cation-adjusted Mueller-Hinton broth (MHB-CA; Lot. BCBW8159; Sigma-Aldrich, Saint

TABLE S1

 S1 Primer used in A. baumannii study

	Sequencing	pmrA -F pmrA -R	ACTGGACATGTTGCACTCTTGT GTGCCCCAAATCAGTCGTTTTT	This study
		pmrB -F1 pmrB -R1	GGCTACCGTTTGGGGCAAT GAGCAGCATCGGCAATAAATTGC	This study
		pmrB -F2 pmrB -R2	TGAACCGTCTTTTTGAGCGCAT GACAGGCTGGGTCGTTTGG	This study
		pmrC -F pmrC -R	TCATTATAGCCATTTGGCTAGGTGC CTCGCTTTAGTTTACATGGGCACAA	(2)
		lpxA -F lpxA -R	GTAGCAGCAACCGCTGAGATTATG AGCCAATATCCAAAATCTGAAGAAGCA	This study
		lpxC -F	GCGTACAATCTATTGAAAGGCAGTG
		lpxC -R	TTAGCCAAGCTTTACTACGTTTGGC	This study
		lpxD -F	GACTGTTGCCTATGACGCTAAGT	This study
		lpxD -R	GCATTGGTAATTCAGGGATGGCA
		Primer	Sequence (5' to 3')	Reference
	RT-qPCR	16S rRNA -F TCAGCTCGTGTCGTGAGATG 16S rRNA -R CCGTAAGGGCCATGATGACT	(1)
		pmrA -F pmrA -R	AGATCCGTCAAAGAGCAGCAA TGCATGAATACGGGCAAGCA	This Study
		pmrB -F pmrB -R	CGACTGATTTGGGGCACCT CTCAGCTGTCCTTTCCGCTA	This study
		pmrC -F pmrC -R	TCGCGTTGAGCAATACCAGA GCAGGTCCATGACTACCCAC	This study
		lpxM -F lpxM -R	TTAGCCGCCAACCCATTCAA ATCGCTATACGCTGCTGAGG	This study
		lpxA -F lpxA -R	TGATCCATCTGCAGTGATTGCT GGCAAACTTCGCCAACACTT	This study
		lpxC -F lpxC -R	ACCGTGGATGGAGGGATTGT TTCCTAAACCGGCAATCGCA	This study
		lpxD -F lpxD -R	TAAAGTAAGCCGTGCGGGTG GGGCAGTGCTTTCTATGCCT	This study

https://clinicaltrials.gov/ Identifier : NCT02682355.

LITERATURE REVIEW PK/PD of Antibiotics

August 2020 Volume 64 Issue 8 e00788-20 aac.asm.org 2

ACKNOWLEDGMENTS

This work was funded by INSERM U1070 Laboratory, Université de Poitiers, and an LPDP scholarship (Indonesia Endowment Fund for Education).

ACKNOWLEDGMENTS

This work was funded by INSERM U1070 laboratory. The authors thank the LPDP scholarship (Indonesia Endowment Fund for Education) for the financial support of H. Ih. ACKNOWLEDGMENTS This work was funded by INSERM U1070 laboratory. The authors thank the LPDP scholarship (Indonesia Endowment Fund for Education) for the financial support of H. Ih. ACKNOWLEDGMENTS Part of this research was presented at the 30 th European Congress of Clinical Microbiology and Infectious Diseases (ECCMID), 18 to 21 April 2020, Paris, France. This work was funded by INSERM U1070 laboratory. The authors thank the LPDP scholarship (Indonesia Endowment Fund for Education) for the financial support of H. Ih.

ABSTRACT Experiments were conducted with polymyxin B and two Klebsiella pneumonia isogenic strains (the wild type, KP_WT, and its transconjugant carrying the mobile colistin resistance gene, KP_MCR-1) to demonstrate that conducting two consecutive time-kill experiments (sequential TK) represents a simple approach to discriminate between pharmacokinetics/pharmacodynamics models with two heterogeneous subpopulations or adaptive resistance.

KEYWORDS Klebsiella pneumoniae, PK/PD model, antibiotic resistance, pharmacodynamics, polymyxin B, sequential time-kill emimechanistic pharmacokinetics/pharmacodynamics (PK/PD) modeling is a modern approach that offers unique opportunities to simulate CFU versus time after antibiotic exposures corresponding to various multiple-dosing strategies (1). Time-kill (TK) experiments constitute a simple and inexpensive approach to generate in vitro data in static conditions for antibiotics PK/PD modeling. After an initial decay of CFU with time, regrowth is frequently observed that can be described by a number of models. However, in the absence of precise mechanistic information, PD models with two stable, heterogeneous subpopulations, i.e., sensitive (S) and resistant (R) (referred to as S/R), would most often demonstrate superiority over models relying on adaptation phenomena (2). Although these models should then be challenged in dynamic (hollow-fiber) conditions, these experimental settings are much more expensive and complex to handle than TK experiments. However, conducting two consecutive TK experiments (sequential TK) may offer a pragmatic alternative. Indeed, the S/R model assumes that initial decay is due to the (S) disappearance and regrowth to (R) selection. However, the (S) and (R) subpopulations are supposed to be stable with time, so no regrowth would be expected after conducting a second TK experiment with the resistant subpopulation bacteria that regrew after the first TK experiment. Such a second regrowth would rather suggest progressive adaptation. Our objective was to confirm experimentally that sequential TK would offer a simple approach to discriminate between regrowth due to heterogeneous subpopulations and adaptive resistance (AR).

Two isogenic isolates were used in this study: a wild-type Klebsiella pneumonia R2292 (KP_WT) and its transconjugant carrying the mobile colistin resistance gene MCR-1 (KP_MCR-1), kindly provided by P. Nordmann (University of Fribourg, Switzerland). This strain was built by transferring the MCR-1 plasmid from MCR-1-positive Escherichia coli isolates as donors (3). TK experiments were conducted in duplicate in

SUPPLEMENTAL MATERIAL FIG S1

Genes relative expression of wild-type (KP_WT) and K. pneumoniae carrying MCR-1 (KP_MCR-1) over PMB from the surviving bacteria in the tail of survival curve from 1 st TK (30 h) and 2 nd TK (60 h) (referred as 1TK and 2TK, respectively). Gene expressions were compared and normalized to their initial isolate before contact to antibiotics (T0). Data are means and error bars represented SD of 3 independent replicates.

Pharmacodynamic modelling of sequential time-kill data exhibiting MCR-1 Klebsiella pneumoniae adaptive resistance towards colistin with arnT gene overexpression

Hariyanto Ih a,c , Alexia Chauzy a , Nicolas Grégoire a,b , Sandrine Marchand a,b , William

ABSTRACT

It is usually considered that bacterial strains carrying the mobile colistin resistance (mcr) gene MCR-1 exhibit low-level resistance, but that adaptive resistance may then develop rapidly. Two-consecutive time-kill (TK) experiments were conducted to investigate adaptive resistance of a transconjugant Klebsiella pneumoniae strain carrying MCR-1 plasmid (KP_MCR-1) to colistin (CST), using the wild-type strain (KP_WT) for comparison. The expression and mutations of genes involved in CST resistance were investigated. KP_WT susceptibility to CST was characterized by a MIC equal to 0.25 mg/L, that did not change with time. KP_MCR-1 was initially less sensitive, with an MIC at 2 mg/L, but adaptive resistance rapidly developed with MICs estimated at 16 and 64 mg/L at the end of the first and second TK, respectively. From a mechanistic standpoint, the most spectacular finding was an approximately 20-fold overexpression of the LPS-modifying gene arnT, in KP_MCR-1 but not in KP_WT, during CST exposure. No mutation was found in LPSmodification genes. From a pharmacodynamic (PD) standpoint, a model-derived instantaneous MIC (MICinstant) was proposed to better capture the rapid adaptive resistance towards CST in KP_MCR-1. In conclusion, this study has shown that the presence of the mcr-1 gene induces a relatively modest decrease of the initial susceptibility to CST in K.

pneumoniae, but that it is also responsible for pronounced adaptive resistance leading to high-level CST resistance. MIC of CST against KP_MCR-1 estimated before treatment initiation, dramatically overestimates the real CST efficacy after several days of treatment, which may induce inappropriate dosing selection and treatments failure.

Estimation and evaluation methods

Model selection was based on objective function value (OFV), relative standard errors (RSEs) of the parameter estimates and goodness of fit plots. When two models were nested, a decrease in OFV of at least 3.84 (chi square 1df p = 0.05) was needed to select the most complex model. The residual errors, the difference between the observed and modelpredicted values at each time point, were additive on a log scale for bacteria counts (log10 cfu/mL).

Observations below the limit of quantification were handled using the M3 method (7).

All analysis were conducted using NONMEM 7.4 (ICON Development Solutions, Ellicott City, MD, USA) with the Laplacian numerical algorithm. under CST pressure while it remains susceptible to PMB. We also showed that selected highlevel colistin resistant in ColR was presumably caused by heteroresistance population associated to loss of LPS production.

DISCUSSION AND PERSPECTIVE

with mathematical PK/PD modelling that constitute a simple experimental approach to simulate colony forming units (CFU) versus time after exposures to antibiotic (225). This generally allows to determine mathematical model where the regrowth is due to two preexisting populations, referred as sensitive and resistant (S/R), adaptive resistance (AR) or even more complex model with two pre-existing populations with adaptive resistance.

However, it is difficult to discriminate the different model, thus the simplest S/R model is preferred to the others independently of the real physiological response (222). These models should be challenged in dynamic conditions, such as hollow-fiber experiments,

where the bacteria are in contact with antibiotic concentrations varying during time like in a patient, but this approach is difficult to set up, expensive and time consuming.

Thereby, we used a simple approach as two consecutive time-kill (TK), referred as sequential TK that is in between: easy to carry out, not expensive and informative enough to improve the mathematical models. Over this approach, no regrowth would be expected after conducting the second TK in heterogenous subpopulations (S/R) by used (R) subpopulation bacteria that regrew after the first TK, otherwise, a second regrowth during the second TK would suggest the progressive adaptation over drugs (226). Compare with single TK, this approach successfully discriminates between models with two heterogenous subpopulations (S/R model) and a homogenous population with adaptive resistance (AR model) as published in article 1, while in article 2, PD models with single susceptible population with no adaptation and AR model were successfully discriminated.

Moreover, this approach coupled with molecular biology studies to describe genomic mutations and/or modifications in gene expression could bring a lot of information about resistance mechanisms.

E. COLI AND K. PNEUMONIAE CARRYING MCR-1

The sequential TK results suggest that both wild-type E. coli and K. pneumoniae were not able to adapt their resistance to polymyxins. They provided two stable heterogenous subpopulations (S) and (R) profiles as shown in article 1 and 3 results, except for wild-type K. pneumoniae during colistin selective pressure that shown a single susceptible population of bacteria as presented in article 2. In contrast, both MCR-1 transconjugants showed a progressive increase of resistance over colistin and polymyxin B after two consecutive TK.

Only the adaptive resistance (AR) model was able to explain of these sequential TK results.

The mcr-1 gene harboring by MCR-1 plasmid expressed in E. coli resulting in the addition of phosphoethanolamine (PEtN) to lipid A (20). Accordingly, the stable regrowth in the 2 nd TK is more expected instead of the second regrowth that suggesting a continuous adaptation with time. To investigate the mechanisms involved behind this adaptation, we started our observation from the LPS-modifying genes chromosomally-mediated polymyxin Furthermore, RT-qPCR analysis was performed to observe these gene expression level change, and pmrE, lpxM, cptA, lpxT and eptB genes that involved in LPS modification were included since these genes activation are pmrA/pmrB and phoP/PhoQ dependent as described in table 4. For E. coli carrying MCR-1, our gene expression results (article 3)