Mario Vaneechoutte & Pieter Deschaght Current developments in anti-biofilm strategies and (assessing...

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Mario Vaneechoutte & Pieter Deschaght

Current developments in anti-biofilm strategies and

(assessing their efficacy with an ex vivo sputum) biofilm models

EYIM Session Microbiology

25 April 2012Paris, France

Chronic infection/Biofilm models to test/predict activity

Many novel antibacterial/anti-biofilm treatment opportunities for chronic infections

are being developed

Clinical trial with patients: cumbersome

1. quorum sensing inhibitors: e.g., furanones, garlick (allicine)

2. antisense RNA strategies to block bacterial transcription and translation

3. antiserum against DNA-binding protein IHF to degrade matrix structure

4. D-amino acids to replace D-ala to degrade matrix structure

5. bacteriophages, with polysaccharide depolymerases to degrade matrix structure

6. iron chelators: e.g., desferoxamine, lactoferrine, conalbumin

7. nitric oxide (NO), toxic to mucoid strains

8. itaconate to block the glyoxylate shunt: waken up persister cells

9. antibiotics combined with the above strategies/compounds

I. Novel anti- (Pseudomonas) biofilm strategies

Activity testing/predicting models

II. Models for predicting the in vivo activity of anti-biofilm treatments

Which model has the highest predictive powerregarding the biofilm eradication succes in the patient?

1. Diffusion antibiogram, starting from planktonic cells

2. Microtiter plate (peg) / glass biofilm susceptibility testing

3. Rotating wall vessel biofilms - Flow cell biofilms

4. Artificial sputum culture with porcine/bovine mucus and herring DNA

5. Co-culture models of ∆F508 cell lines and P. aeruginosa

6. Animal infection models

7. Ex vivo biofilm sputum model Patient

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1. quorum sensing inhibitors: e.g., furanones, garlick (allicine)

JAC 53: 1054-1061

2004

Res. Microbiol. 160: 144-151.

2009


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MotA, a cytoplasmic membrane protein generates the force necessary to drive the flagellum is one of the key regulation factors in the initial period of biofilm formation.

Inhibition of P. aeruginosa biofilm formation by the cell-penetrating peptide (KFF)3K + anti-motA-Peptide Nucleic Acid (PNA)

2. antisense strategies to block bacterial transcription and translation

Hu et al. 2011. World J Microbiol Biotechnol. DOI 10.1007/s11274-011-0658-x

No treatment

1 µM (KFF)3K-PNA

5 µM (KFF)3K-PNA

10 µM (KFF)3K-PNA


Biofilm formation

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DNABII family of proteins have strong structural influence on intracellular DNA.DNABII is also critical for the integrity of the EPS matrix of biofilms that contain eDNA.

In vitro: DNABII rapidly disrupts the biofilm EPS formed by multiple human pathogens in vitro. Synergism with otherwise ineffective traditional antimicrobial approaches in vitro.

3. antiserum against DNA-binding protein IHF

Extracellular DNA (eDNA) is a key component of EPS in many pathogenic biofilms.Whitchurch et al. 2002. Extracellular DNA required for bacterial biofilm formation. Science 295: 1487 pulmozyme (rh DNAse)

Goodman et al. 2011. Mucosal Immunol 4: 625-637.


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Viable planktonic bacteria released from a nontypeable Haemophilus influenzae (NTHI) biofilmafter treatment with anti-DNAIIB (= anti-IHF)

I. Novel anti- (Pseudomonas) biofilm strategies3. antiserum against DNA-binding protein IHF

Goodman et al. 2011. Mucosal Immunol 4: 625-637.

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Kolodkin-Gal et al. 2010. Science 328: 627-629.

Bacillus subtilis

I. Novel anti- (Pseudomonas) biofilm strategies4. D-amino acids (D-AAs)

D-AAs: D-tyrosine, D-leucine, D-tryptophan, and D-methionine inhibit biofilm formation + degrade biofilm.

In contrast, the corresponding L-isomers were inert in the biofilm-inhibition assay.

Individual D-AAs varied in their activity:D-tyrosine was more effective (at 3 µM) than D-methionine (at 2 mM)Mixture of the 4 D-AAs was most potent: 10 nM

Bacteria produce D-amino acids (D-AAs) in stationary phase/mature biofilm D-AAs replace D-ala in cell wall, anchor for TasA fibers (Bacillus subtilis) TasA can no longer bind to cell wall [Biofilm matrix = EPS + amyloid fibers composed of the protein TasA] Biofilm disruption (see also our results with the EVSM)

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I. Novel anti- (Pseudomonas) biofilm strategies5. bacteriophages

Hughes et al. 1998a. J Appl Microbiol 85: 583-590.Hughes et al. 1998.b. Microbiol 144: 3039–3047

Lytic zone

EPS degradation zone

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Sutherland et al. 2004. FEMS Microbiol. 232: 1-6.


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Glonti et al. 2010. J Appl Microbiol 108: 695-702.

Khawaldeh et al. 2011. J Med Microbiol 60: 1697-1700.


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6. iron chelators: desferoxamine, lactoferrin, conalbumin, EDTA, EGTA


Moreau-Marquis et al. 2008. Am J Physiol Lung Cell Mol Physiol 295: L25–L37Iron in CF lung bronchoalveolar lavage (BAL) fluid, CF sputum: 8 µMBAL isolated from healthy patients: 0.018 µM due to intrinsic iron sequestration problem of ∆F508 CFTR cells

O'May et al. 2009. J Med Microbiol 58:765-773.

"In addition, clinical strains responded differently to different chelators."

Musk & Hergenrother. 2008. J Appl Microbiol 105: 380-388.

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6. iron chelators: e.g., desferoxamine, lactoferrine, conalbumin

Culture of P. aeruginosa biofilm, during 6 hours, on ∆F508 airway cellsLive/Dead staining + CLSM.

No treatment Desferoxamine 400 µg/ml (DFO)

Tobramycine Tobramycine 1000 µg/ml + DFO


Moreau-Marquis et al. 2009. Am J Respir Cell Mol Biol 41: 305-313.

See also our results with EVSM

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7. nitric oxide

at pH 6.5, 15 mM NO2– kills mucA mutant P. aeruginosa in CF airway conditions after 16 days

has no adverse effects on cultured human airway epithelia in vitro.

In this study, we believe that we have discovered the Achilles’ heel of the formidable mucoid form of P. aeruginosa, which could lead to improved treatment for CF airway disease.


Yoon et al. 2006. J Clin Invest 116: 436-446.

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P. aeruginosa is capable of robust anaerobic growth by respiration using nitrate (NO3

–) or nitrite (NO2–) as terminal electron acceptors.

NO3- NO2- NO N2O N2

NAR NIR NOR NOS

Mucoid strains aremost sensitive to HNO2

7. nitric oxide


CF ASL and sputum concentrations of NO3– and NO2

–: up to 600 μM final electron acceptors for anaerobic respiration and growth by P. aeruginosa P. aeruginosa uses NAR and NIR to reduce NO3

– to NO2– to NO

increased levels of NO, a toxic intermediate of NO3– and NO2

– reduction synthesis of protective NO reductase (NOR) by P. aeruginosa.

Leukocyte attacks + leukocyte killing by P. aeruginosa rhamnolipids ROS

mucA mutations alginate production mucoid conversion

NOR sensitivity to HNO2

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8. blocking the glyoxylate shunt with itaconate

Persister cells use the glyoxylate shunt instead of the Krebs cycle


Krebs cycle reducing agents: NADH, FADH2 18 ATP rapid growth

ROS Oxydative stress Bactericidal

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8. blocking the glyoxylate shunt with itaconateLindsey et al. 2008. Virulence determinants from a cystic fibrosis isolate of Pseudomonas aeruginosa include isocitrate lyase. Microbiol 154: 1616-1627.


Persister cellsswitch off Krebs cycle

switch to glyoxylate shunt low NADH/FADH2 production

low ATP production slow growth (dormancy) intrinsic AB resistance

low ROS production high resistance to killing

Isocitrate lyase is absent in man good antimicrobial target inhibition by itaconate:

itaconate

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9. novel antibiotic formulations and combinations

AB + AB: Tré-Hardy et al. 2009. Int J Antimicrob Agents 34: 370-374.

AB + AMP: Nagant et al. 2010. Appl Microbiol Biotechnol 88: 251-263


AB+ Phage: Comeau et al. 2008. PLoS ONE 2(8): e799.

II. Models for predicting the in vivo activity of anti-biofilm treatments

Which model has the highest predictive powerregarding the biofilm eradication succes in the patient?

1. Diffusion antibiogram, starting from planktonic cells

2. Microtiter plate (peg) biofilm susceptibility testing

3. Rotating wall vessel biofilms - Flow cell biofilms

4. Artificial sputum culture with bovine mucus

5. Co-culture models of CF cell lines and P. aeruginosa

6. Animal infection models

7. Ex vivo biofilm sputum modelPatient

II. II. Models for predicting the in vivo efficacy of anti-biofilm treatments

1. Diffusion antibiogram for P. aeruginosa, cultured from sputum of CF patients: = starting from planktonic cells: Foweraker et al. (2005)

irreproducible within and between labs even same colony morphology yields different susceptibility patterns

limited correlation between susceptibility and clinical outcome

Foweraker et al. 2005. JAC 55: 921-927.

2. Microtiter biofilm-based susceptibility testing: Tré-Hardy et al. 2009. Int J Antimicrob Agents 33: 40-45.

Observations: strong differences between planktonic cells and biofilm grown cells

strong differences between young and mature biofilms

II. Models for predicting the in vivo efficacy of anti-biofilm treatments

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2. Microtiter biofilm-based susceptibility testing

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Moskowitz et al. 2011. Ped Pulmonol 46: 184-192.Set up: 39 participants. Treated with 14-day courses of two antibiotics, that were selected on basis of diffusion antibiogram (planktonic cells) or on basis of microtiter biofilm susceptibility testing results

Conclusions: In this pilot study, antibiotic regimens based on biofilm testing did not differ significantly from regimens based on conventional testing

in terms of microbiological and clinical responses.

2. Microtiter biofilm-based susceptibility testing


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3. Rotating wall vessel technology: low shear

Crabbé et al. 2009. Environm Microbiol

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10 mg/ml porcine stomach mucin1.4 mg/ml herring sperm DNA


4. Artificial sputum medium

5. Co-cell culture with Pseudomonas aeruginosa

Observations: biofilm formation on lung epithelial cell culture vs biofilm on abiotic surfaces (glass): 1500-fold more production of biofilm 25-fold increase of resistance to tobramycin

Limitations: Long term infection difficult: cells rapidly killed by P. aeruginosa No mucus compound No human immunity compound Limited complexity of microflora: 1 species, 1 strain (PAO1) Many parameters, such as coating, cell line, cell maturity, buffer, ... influence outcome


Moreau-Marquis et al. 2008. Am J Physiol Lung Cell Mol Physiol 295: L25-L37.

6. Animal infection models: CFTR knockouts of mouse, rat, pig

Limitations: Expensive, cumbersome, ethical considerations And still: Limited chronic colonization (artificial: sea weed alginate beads) No human cells, mucus, immune compounds

No original biofilm



In summary: Whatever modification to the susceptibility testing biofilm model: planktonic growth - biofilm young biofilm - mature biofilm plastic biofilm - cell line associated biofilm young cell lines - mature cell lines (nonchronic) animal infection modelsAll have their merits, but very different predictions about biofilm formation and biofilm susceptibility

Which one predicts most reliably the susceptibility of the P. aeruginosa biofilm in the patient?

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Limitations of current biofilm models:

Each model or variation of parameters leads to strongly different predictions about biofilm formation and biofilm susceptibility

Original biofilm structure (mucus associated microcolonies) as in patient is absent

Multiple genotypes and phenotypes of P. aeruginosa are absent (usually PAO1)

Extracellular human DNA is absent

Mucus from patient is absent

Leukocytes, cytokines of patient are absent

II. Models for predicting the in vivo efficacy of anti-biofilm treatments7. Ex vivo sputum biofilm model

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Time for a different approach?

1. Add the anti-Pseudomonas - anti-biofilm treatment (at break point concentration) directly to P. aeruginosa colonized sputum of CF patients

= address the original biofilm in the original patient environment

2. Monitor the effect of the treatment on the P. aeruginosa load in comparison with the P. aeruginosa load of untreated sputum

7. the Ex Vivo Sputum Biofilm Model (EVSM)


Is using sputum a valid approach for testing susceptibility of P. aeruginosa biofilms in the CF airways?

This depends on the localisation of the chronic biofilm colonisation/infection

1. At the epithelium of lungs?group of Gerald PierFoweraker. 2009. Recent advances in cystic fibrosis. Brit Med Bull 89: 93-110.

or?2. In the lumen of the conductive airways, within the mucus layer? sputum


Percentage of bacteria at distances of 5-17 and 2-5 µm

from epithelial surface of lungs from 9 CF patients

Where is the chronic biofilm colonisation/infection located?

MAMs: mucus associated microcolonies


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Bjarnsholt et al. 2009. Ped Pulmonol 44: 547-558.

Expectorated sputum contains the persistent biofilm fraction from CF airways


Results are very patient dependent Need for personalized approach

Strains isolated from sputum and recultured (red) are rapidly killed Same strains in original sputum associated biofilm (purple) are not

DFO is not very effective in original sputum biofilm Airway model of Moreau-Marquis et al. (2009)Tobra + EDTA can eradicate all cultivable biofilm cells in some patients

Results with ex vivo biofilm model(culture based analysis)

No tre

atm

ent (

0 h)

No tre

atm

ent (

24 h

)DFO

EDTA TM

DFO + T

M

EDTA + T

M1.00E+00

1.00E+01

1.00E+02

1.00E+03

1.00E+04

1.00E+05

1.00E+06

1.00E+07

1.00E+08

1.00E+09

Patient 14

Cel

ls/m

l (l

og

)

No tre

atm

ent (

0 h)

No tre

atm

ent (

24 h

)DFO

EDTA TM

DFO + T

M

EDTA + T

M1.00E+00

1.00E+01

1.00E+02

1.00E+03

1.00E+04

1.00E+05

1.00E+06

1.00E+07

1.00E+08

1.00E+09

Patient 7

Cel

ls/m

l (l

og

)

36

1.00E+06

1.00E+07

1.00E+08

1.00E+09

levend Tobra Tobra+ D-Tyr

Tobra+ D-Met

D-Tyr D-Met Tobra+ D-Tyr +

D-Met

D-Tyr+ D-Met

Behandeling

Bact

erië

n/m

l

400 µg/ml Tobra

1000 µg/ml Tobra

Results with ex vivo biofilm model(culture based analysis)

Effects of Tobra (400 vs 1000 µg/ml) and D-amino acids (3 µM)added to patient sputum colonized with P. aeruginosa


Methods to assess treatment efficacy

A. Troublesome approaches: 1. Culture: only cultivable cells are assessed, not dormant biofilm part. Workload high.

2. DNA-qPCR: also dead cells are assessed Treatment effects are not observable.

3. Reverse transcription qPCR: cumbersome: - RNA instability - different transcription levels of different genes in biofilm-associated dormant and planktonic cells.

4. Life/Dead staining: too much interference of free (leukocyte) DNA in sputum

B. Possible approaches: 1. FISH biofilm structure is assessed. Quantification troublesome?

2. PMA + DNA-qPCR: All living cells but no dead cells are quantified.


Nocker A, Cheung CY, Kamper AK. 2006. Comparison of propidium monoazide with ethidium monoazide for differentiation of live vs. dead bacteria by selective removal of DNA from dead cells. J Microbiol Meth 67: 310-320.

PMA + DNA-qPCR: All living cells and no dead cells are quantified


Advantages of using colonized sputum

Readily available in large quantities

Personalized informationOther treatments of patient present (mucolytics, potentiators, correctors)Differences in genetic CFTR background of CF patients presentDifferences in modifier genes & immune respons of CF patients presentDifferences in status of colonisation (recent, long-term) present

Most probably: highest predictive power regarding treatment success in patient.


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Limitations of the ex vivo sputum modelUnequal distribution of colonisation? When obtained after physiotherapy, MAM distribution turns out to be fairly even

The EVSM is not suited

to find out how reduced P. aeruginosa /bacterial colonisation affects patient health.

to assess the side effects of antibacterial treatments on the airway epithelium: ex vivo primary cell lines might be most informative and most personalized.

to assess CFTR corrector and potentiator effects ex vivo primary cell lines might be most informative and most personalized.


Special thanks to Pieter Deschaght & Leen Van Simaey (LBR)

the sputum donors

the nursing staff of MucoGent, University Hospital Gent, BelgiumLinda Mahieu, Marleen Vanderkerken and Ann Raman

MucoVereniging België

Slides available at: http://users.ugent.be/~mvaneech/[email protected]

The ex vivo sputum model

http://users.ugent.be/~mvaneech/LBR.htm




mailto:[email protected]

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