mario vaneechoutte & pieter deschaght current developments in anti-biofilm strategies and
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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
I. Novel anti- (Pseudomonas) biofilm strategies
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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
I. Novel anti- (Pseudomonas) biofilm strategies
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.
I. Novel anti- (Pseudomonas) biofilm strategies
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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. bacteriophagesHughes 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.
I. Novel anti- (Pseudomonas) biofilm strategies5. bacteriophages
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Glonti et al. 2010. J Appl Microbiol 108: 695-702.
Khawaldeh et al. 2011. J Med Microbiol 60: 1697-1700.
I. Novel anti- (Pseudomonas) biofilm strategies5. bacteriophages
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6. iron chelators: desferoxamine, lactoferrin, conalbumin, EDTA, EGTA
I. Novel anti- (Pseudomonas) biofilm strategies
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
I. Novel anti- (Pseudomonas) biofilm strategies
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.
I. Novel anti- (Pseudomonas) biofilm strategies
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 oxideI. Novel anti- (Pseudomonas) biofilm strategies
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
I. Novel anti- (Pseudomonas) biofilm strategies
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.
I. Novel anti- (Pseudomonas) biofilm strategies
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
I. Novel anti- (Pseudomonas) biofilm strategies
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 model Patient
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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II. Models for predicting the in vivo efficacy of anti-biofilm treatments
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
II. Models for predicting the in vivo efficacy of anti-biofilm treatments
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II. Models for predicting the in vivo efficacy of anti-biofilm treatments
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
II. Models for predicting the in vivo efficacy of anti-biofilm treatments
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
II. Models for predicting the in vivo efficacy of anti-biofilm treatments
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
II. Models for predicting the in vivo efficacy of anti-biofilm treatments
II. Models for predicting the in vivo efficacy of anti-biofilm treatments
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)
II. Models for predicting the in vivo efficacy of anti-biofilm treatments
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
II. Models for predicting the in vivo efficacy of anti-biofilm treatments7. Ex vivo sputum biofilm model
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
II. Models for predicting the in vivo efficacy of anti-biofilm treatments7. Ex vivo sputum biofilm model
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Bjarnsholt et al. 2009. Ped Pulmonol 44: 547-558.
Expectorated sputum contains the persistent biofilm fraction from CF airways
II. Models for predicting the in vivo efficacy of anti-biofilm treatments7. Ex vivo sputum biofilm model
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 trea
tmen
t (0 h)
No trea
tmen
t (24 h
)DFO
EDTA TM
DFO + TM
EDTA + TM1.00E+001.00E+011.00E+021.00E+031.00E+041.00E+051.00E+061.00E+071.00E+081.00E+09
Patient 14
Cells
/ml (
log)
No trea
tmen
t (0 h)
No trea
tmen
t (24 h
)DFO
EDTA TM
DFO + TM
EDTA + TM
1.00E+001.00E+011.00E+021.00E+031.00E+041.00E+051.00E+061.00E+071.00E+081.00E+09
Patient 7
Cells
/ml (
log)
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
Bac
terië
n/m
l 400 µg/ml Tobra1000 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
II. Models for predicting the in vivo efficacy of anti-biofilm treatments7. Ex vivo sputum biofilm model
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.
II. Models for predicting the in vivo efficacy of anti-biofilm treatments7. Ex vivo sputum biofilm model
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
II. Models for predicting the in vivo efficacy of anti-biofilm treatments7. Ex vivo sputum biofilm model
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.
II. Models for predicting the in vivo efficacy of anti-biofilm treatments7. Ex vivo sputum biofilm model
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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.
II. Models for predicting the in vivo efficacy of anti-biofilm treatments7. Ex vivo sputum biofilm model
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/LBR.htmMario.Vaneechoutte@UGent.be
The ex vivo sputum model
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