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What Is the ‘Minimum Inhibitory Concentration’ (MIC) of Pexiganan Acting on Escherichia coli?—A Cautionary Case Study

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Biophysics of Infection

Part of the book series: Advances in Experimental Medicine and Biology ((AEMB,volume 915))

Abstract

We measured the minimum inhibitory concentration (MIC) of the antimicrobial peptide pexiganan acting on Escherichia coli , and found an intrinsic variability in such measurements. These results led to a detailed study of the effect of pexiganan on the growth curve of E. coli, using a plate reader and manual plating (i.e. time-kill curves). The measured growth curves, together with single-cell observations and peptide depletion assays, suggested that addition of a sub-MIC concentration of pexiganan to a population of this bacterium killed a fraction of the cells, reducing peptide activity during the process, while leaving the remaining cells unaffected. This pharmacodynamic hypothesis suggests a considerable inoculum effect, which we quantified. Our results cast doubt on the use of the MIC as ‘a measure of the concentration needed for peptide action’ and show how ‘coarse-grained’ studies at the population level give vital information for the correct planning and interpretation of MIC measurements.

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Notes

  1. 1.

    See http://datashare.is.ed.ac.uk/handle/10283/1885 to access relevant data on which this article is based.

  2. 2.

    Continuing the experiment to 72 did not change the observed growth/no-growth pattern.

  3. 3.

    This is perhaps unsurprising given that MG1655 is a laboratory strain that has been described as ‘deceitful delinquents growing old disgracefully’ (Hobman et al. 2007).

  4. 4.

    E.g., no replicates are suggested in the guidelines for loading a 96-well plate for testing a range of agents on E. coli and Salmonella isolates in a WHO project (Hendriksen 2010).

  5. 5.

    See Fig. 2 in Hendriksen (2010). If, alternatively, we identify our wells C3, C5 and C10, Fig. 4.1, as contaminated, then the ‘true MIC’ would be taken to be 2.5 M.

  6. 6.

    We detected growth in a well at 2 × 107 cells/ml, similar to what was reported previously for multi-well plate readers (Pin and Baranyi 2006; Métris et al. 2006). Lengthened detection times due to peptide action recalls the ‘virtual colony count’ (VCC) approach developed to measure defensin activity (Ericksen et al. 2005). However, unlike in VCC, bacteria in our case were exposed to peptides in their growth medium rather than grown in a peptide-free medium after exposure.

  7. 7.

    Cells with the shortest single cell lag times dominate the population lag (Baranyi 1998), which can be crudely calculated to be ~10 min after the transfer procedure from liquid culture to agar.

  8. 8.

    Note that 5 cells/ml ≡ 1 cell/well, so that the fraction of growing wells is <1 at zero pexiganan.

  9. 9.

    We have seen such aggregation in optical microscopy (data not shown).

References

  • Abraham JM, Freitag CS, Clements JR, Eisenstein BI (1985) An invertible element of DNA controls phase variation of type 1 fimbriae of Escherichia coli. Proc Natl Acad Sci USA 82:5724–5727

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Aminov RI (2010) A brief history of the antibiotic era: lessons learned and challenges for the future. Front Microbiol 1:art. 134

    Google Scholar 

  • Annis DH, Craig BA (2005) The effect of interlaboratory variability on antimicrobial susceptibility determination. Diagn Microbiol Infect Dis 53:61–64

    Article  CAS  PubMed  Google Scholar 

  • Baraban L, Bertholle F, Salverda MLM, Bremond N, Panizza P, Baudry J, de Visser JAGM, Bibette J (2011) Millifluidic droplet analyser for microbiology. Lab Chip 11:4057–4062

    Article  CAS  PubMed  Google Scholar 

  • Baranyi J (1998) Comparison of stochastic and deterministic concepts of bacterial lag. J Theor Biol 192(3):403–408

    Article  PubMed  Google Scholar 

  • Blattner F, Plunkett G, Bloch C, Perna N, Burland V, Riley M, ColladoVides J, Glasner J, Rode C, Mayhew G, Gregor J, Davis N, Kirkpatrick H, Goeden M, Rose D, Mau B, Shao Y (1997) The complete genome sequence of Escherichia coli K-12. Science 277:1453–1462

    Article  CAS  PubMed  Google Scholar 

  • CLSI (2012) Methods for Dilution Antimicrobial Susceptibility Tests for Bacteria That Grow Aerobically; Approved Standard, 9th edition. CLSI document M07-A9. Clinical and Laboratory Standards Institute, Wayne, PA

    Google Scholar 

  • Fjell CD, AH J, Hancock REW, Schneider G (2012) Designing antimicrobial peptides: form follows function. Nat Rev Drug Discov 11:37–51

    CAS  Google Scholar 

  • Ericksen B, Wu Z, Lu W, Lehrer RI (2005) Antibacterial activity and specificity of the six human α-defensins. Antimicrob. Agents Chemother. 49:269–275

    Google Scholar 

  • Fuchs PC, Barry AL, Brown SD (1998) In vitro antimicrobial activity of MSI-78, a magainin analog. Antimicrob Agents Chemother 42:1213–1216

    CAS  PubMed  PubMed Central  Google Scholar 

  • Ge Y, MacDonald DL, Holroyd KJ, Thornsberry C, Wexler H, Zasloff M (1999) In vitro antibacterial properties of pexiganan, an analog of magainin. Antimicrob Agents Chemother 43:782–788

    CAS  PubMed  PubMed Central  Google Scholar 

  • Gottler LM, Ramamoorthy A (2009) Structure, membrane orientation, mechanism, and function of pexiganan: a highly potent antimicrobial peptide designed from magainin. Biochim Biophys Acta 1788:1680–1686

    Article  CAS  PubMed  Google Scholar 

  • Gottler LM, Lee HY, Shelburne CE, Ramamoorthy A, Marsh ENG (2008) Using fluorous amino acids to modulate the biological activity of an antimicrobial peptide. ChemBioChem 9:370–373

    Article  CAS  PubMed  Google Scholar 

  • Hendriksen RS (ed) (2010) Laboratory Protocols: Level 1 Training Course: MIC determination by broth dilution using Sensititre. No publisher given, available online at http://goo.gl/57Pu7F. Accessed Sat Mar 19 15:45:46 2016

  • Hobman JL, Penn CW, Pallen MJ (2007) Laboratory strains of Escherichia coli: model citizens or deceitful delinquents growing old disgracefully? Mol Microbiol 64:881–885

    Article  CAS  PubMed  Google Scholar 

  • Jones E, Smart A, Bloomberg G, Burgess L, Millar M (1994) Lactoferricin, a new antimicrobial peptide. J Appl Bact 77:208–214

    Article  CAS  Google Scholar 

  • Lerouge I, Vanderleyden J (2002) O-antigen structural variation: mechanisms and possible roles in animal/plantâmicrobe interactions. FEMS Microbiol Rev 26:17–47

    Article  CAS  PubMed  Google Scholar 

  • Levison ME, Pitsakis PG, May PL, Johnson CC (1993) The bactericidal activity of magainins against Pseudomonas aeruginosa and Enterococcus faecium. J Antimicrob Chemother 32:577–585

    Article  CAS  PubMed  Google Scholar 

  • Matsuzaki K, Mitani Y, Akada KY, Murase O, Yoneyama S, Zasloff M, Miyajima K (1998) Mechanism of synergism between antimicrobial peptides magainin 2 and PGLa. Biochemistry 37:15,144–53

    Google Scholar 

  • McGrath DM, Barbu EM, Driessen WHP, Lasco TM, Tarrand JJ, Okhuysen PC, Kontoyiannis DP, Sidman RL, Pasqualini R, Arap W (2013) Mechanism of action and initial evaluation of a membrane active all-D-enantiomer antimicrobial peptidomimetic. Proc Natl Acad Sci USA 110:3477–3482

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Melo MN, Ferre R, Castanho MARB (2009) Antimicrobial peptides: linking partition, activity and high membrane-bound concentrations. Nat Rev Microbiol 7(3):245–250

    Article  CAS  PubMed  Google Scholar 

  • Métris A, Le Marc Y, Elfwing A, Ballagi A, Baranyi J (2005) Modelling the variability of lag times and the first generation times of single cells of E. coli. Int J Food Microbiol 100(1):13–19

    Article  PubMed  Google Scholar 

  • Métris A, George SM, Baranyi J (2006) Use of optical density detection times to assess the effect of acetic acid on single-cell kinetics. Appl Environ Microbiol 72(10):6674–6679

    Article  PubMed  PubMed Central  Google Scholar 

  • Moiset G, Cirac AD, Stuart MCA, Marrink SJ, Sengupta D, Poolman B (2013) Dual action of BPC194: a membrane active peptide killing bacterial cells. PLoS ONE 8:e61541

    Google Scholar 

  • Moore A (2003) The big and small of drug discovery. EMBO Rep 4:114–117

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Perron GG, Zasloff M, Bell G (2006) Experimental evolution of resistance to an antimicrobial peptide. Proc Biol Sci/Royal Soc 273:251–256

    Article  CAS  Google Scholar 

  • Pin C, Baranyi J (2006) Kinetics of single cells: observation and modeling of a stochastic process. Appl Environ Microbiol 72:2163–2169

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Pius J, Morrow MR, Booth V (2012) H solid-state nuclear magnetic resonance investigation of whole Escherichia coli interacting with antimicrobial peptide MSI-78. Biochemistry 51:118–125

    Article  CAS  PubMed  Google Scholar 

  • Rakowska PD, Jiang H, Ray S, Pyne A, Lamarre B, Carr M, Judge PJ, Ravi J, Gerling UIM, Koksch B, Martyna GJ, Hoogenboom BW, Watts A, Crain J, Grovenor CRM, Ryadnov MG (2013) Nanoscale imaging reveals laterally expanding antimicrobial pores in lipid bilayers. Proc Natl Acad Sci USA 110:8918–8923

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Ramamoorthy A, Thennarasu S, Lee DK, Tan A, Maloy L (2006) Solid-state NMR investigation of the membrane-disrupting mechanism of antimicrobial peptides MSI-78 and MSI-594 derived from magainin 2 and melittin. Biophys J 91:206–216

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Rasch M, Métris A, Baranyi J, Bjørn Budde B (2007) The effect of reuterin on the lag time of single cells of Listeria innocua grown on a solid agar surface at different pH and NaCl concentrations. Int J Food Microbiol 113(1):35–40

    Article  CAS  PubMed  Google Scholar 

  • Schuurmans JM, Nuri Hayali AS, Koenders BB, ter Kuile BH (2009) Variations in MIC value caused by differences in experimental protocol. J Microbiol Meth 79:44–47

    Article  CAS  Google Scholar 

  • Spindler EC, Hale JDF, Giddings TH, Hancock REW, Gill RT (2011) Deciphering the mode of action of the synthetic antimicrobial peptide Bac8c. Antimicrob Agents Chemother 55:1706–1716

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Udekwu KI, Parrish N, Ankomah P, Baquero F, Levin BR (2009) Functional relationship between bacterial cell density and the efficacy of antibiotics. J Antimicrob Chemother 63:745–757

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Wakamoto Y, Dhar N, Chait R, Schneider K, Signorino-Gelo F, Leibler S, McKinney JD (2013) Dynamic persistence of antibiotic-stressed mycobacteria. Science (New York, NY) 339:91–95

    Article  CAS  Google Scholar 

  • Wiegand I, Hilpert K, Hancock REW (2008) Agar and broth dilution methods to determine the minimal inhibitory concentration (MIC) of antimicrobial substances. Nat Protoc 3:163–175

    Article  CAS  PubMed  Google Scholar 

  • Wimley WC (2010) Describing the mechanism of antimicrobial peptide action with the interfacial activity model. ACS Chem Biol 5:905–917

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

AKJ was funded by an EPSRC studentship. JSL was funded by the National Physical Laboratory and SUPA. LR and MGR were funded by the UK Department of Business, Innovation and Skills. WCKP was funded by EPSRC Programme Grant EP/J007404/1. We thank Simon Titmuss for illuminating discussions, Angela Dawson for assistance in biological lab work and Vincent Martinez for assistance with data analysis.

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Authors and Affiliations

  1. SUPA and School of Physics and Astronomy, The University of Edinburgh, Peter Guthrie Tait Road, Edinburgh, EH9 3FD, Scotland, UK

    Alys K. Jepson, Jana Schwarz-Linek & Wilson C. K. Poon

  2. National Physical Laboratory, Hampton Road, Teddington, TW11 0LW, UK

    Lloyd Ryan & Maxim G. Ryadnov

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  1. Alys K. Jepson
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  2. Jana Schwarz-Linek
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  3. Lloyd Ryan
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  4. Maxim G. Ryadnov
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  5. Wilson C. K. Poon
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Correspondence to Wilson C. K. Poon .

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  1. Biological Physical Sciences Institute, University of York, York, United Kingdom

    Mark C. Leake

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Jepson, A.K., Schwarz-Linek, J., Ryan, L., Ryadnov, M.G., Poon, W.C.K. (2016). What Is the ‘Minimum Inhibitory Concentration’ (MIC) of Pexiganan Acting on Escherichia coli?—A Cautionary Case Study. In: Leake, M. (eds) Biophysics of Infection. Advances in Experimental Medicine and Biology, vol 915. Springer, Cham. https://doi.org/10.1007/978-3-319-32189-9_4

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