1887

Abstract

Quantification of bacterial load in tissue homogenates in pharmacodynamic studies is cumbersome and time-consuming.

We therefore developed a new method for quantifying bacterial load in tissue homogenates of animals treated with a β-lactam and β-lactamase inhibitor using growth curves.

The log colony-forming units (c.f.u.) ml of 184 thigh and lung homogenates from female CD-1 mice infected intranasally and intramuscularly with 4 , 4 , 3 and 2 strains treated with a β-lactam drug and tazobactam were calculated using the standard approach of serial quantitative cultures and analysis of growth curves. Growth curves were obtained with continuous (every 10 min) monitoring of optical density at 630 nm (OD) after 20 µl tissue homogenates were inoculated in total volume of 200 µl Mueller–Hinton broth in 96-well microtitration plates and incubated at 37 °C for 18 h.

The best correlation between log c.f.u. ml determined with the serial quantitative cultures and growth curves was found at the time point corresponding to an OD of 0.25 increase above the baseline OD (average of first five timepoints) ( =0.918–0.999). The median (range) differences between the two methods was −0.19 (−1.79–1.69) with 86–97 % of all isolates and species being within 1 log c.f.u. ml with 1 h hands-on-time and <13 h of incubation for 96 samples. Pharmacodynamic analysis showed similar dose–response relationships and 1 log kill dose estimations (paired -test, =0.112).

The new technique resulted in comparable c.f.u. counts to those for the standard serial dilution/culture technique with minimal hands-on and turnaround times.

Funding
This study was supported by the:
  • Johan W. Mouton , AICuris , (Award NA)
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2020-03-31
2020-06-04
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References

  1. Hawkey PM. Multidrug-resistant gram-negative bacteria: a product of globalization. J Hosp Infect 2015; 89:241–247 [CrossRef][PubMed][PubMed]
    [Google Scholar]
  2. Medina E, Pieper DH. Tackling threats and future problems of multidrug-resistant bacteria. In: Current topics in microbiology and immunology 2016 pp 3–33
    [Google Scholar]
  3. Berkhout J, Melchers MJ, van Mil AC, Seyedmousavi S, Lagarde CM et al. Pharmacokinetics and penetration of ceftazidime and avibactam into epithelial lining fluid in thigh- and lung-infected mice. Antimicrob Agents Chemother 2015; 59:2299–2304 [CrossRef][PubMed]
    [Google Scholar]
  4. Melchers MJ, van Mil AC, Lagarde C, den Hartigh J, Mouton JW. Pharmacodynamics of cefepime combined with tazobactam against clinically relevant Enterobacteriaceae in a neutropenic mouse thigh model. Antimicrob Agents Chemother 2017; 61:e00267–17 [CrossRef][PubMed][PubMed]
    [Google Scholar]
  5. Conn HW, Conn HJ. Bacteriology: A study of microorganisms and their relation to human welfare, 3rd ed. Baltimore: Williams & Wilkins; 1923 p 54
    [Google Scholar]
  6. Steen HB, Boye E, Skarstad K, Bloom B, Godal T et al. Applications of flow cytometry on bacteria: cell cycle kinetics, drug effects, and quantitation of antibody binding. Cytometry 1982; 2:249–257 [CrossRef][PubMed][PubMed]
    [Google Scholar]
  7. Hsieh K, Zec HC, Chen L, Aniruddha M, Mach KE et al. Simple, fast, and precise counting of viable bacteria by resazurin-amplified picoarray detection simple, fast, and precise counting of viable bacteria by Resazurin-Amplified Picoarray detection. Anal Chem 2018
    [Google Scholar]
  8. Hazan R, Que Y-A, Maura D, Rahme LG. A method for high throughput determination of viable bacteria cell counts in 96-well plates. BMC Microbiol 2012; 12:1 [CrossRef][PubMed]
    [Google Scholar]
  9. Lyons SR, Griffen AL, Leys EJ. Quantitative real-time PCR for Porphyromonas gingivalis and total bacteria. J Clin Microbiol 2000; 38:2362–2365 [CrossRef][PubMed]
    [Google Scholar]
  10. Begot C, Desnier I, Daudin JD, Labadie JC, Lebert A. Recommendations for calculating growth parameters by optical density measurements. J Microbiol Methods 1996; 25:225–232 [CrossRef]
    [Google Scholar]
  11. Melchers MJ, Mavridou E, Van Mil AC, Lagarde C, Mouton JW. Pharmacodynamics of ceftolozane combined with tazobactam against Enterobacteriaceae in a neutropenic mouse thigh model; 2016; 607272–7279
  12. Melchers MJ, Mavridou E, Seyedmousavi S, van Mil AC, Lagarde C et al. Plasma and epithelial lining fluid pharmacokinetics of ceftolozane and tazobactam alone and in combination in mice. Antimicrob Agents Chemother 2015; 59:3373–3376 [CrossRef][PubMed]
    [Google Scholar]
  13. Ott SJ, Musfeldt M, Ullmann U, Hampe J, Schreiber S. Quantification of intestinal bacterial populations by real-time PCR with a universal primer set and minor groove binder probes: a global approach to the enteric flora. J Clin Microbiol 2004; 42:2566–2572 [CrossRef][PubMed]
    [Google Scholar]
  14. Quigley L, O'Sullivan O, Beresford TP, Ross RP, Fitzgerald GF et al. Molecular approaches to analysing the microbial composition of raw milk and raw milk cheese. Int J Food Microbiol 2011; 150:81–94 [CrossRef][PubMed]
    [Google Scholar]
  15. Nocker A, Cheung C-Y, Camper AK. Comparison of propidium monoazide with ethidium monoazide for differentiation of live vs. dead bacteria by selective removal of DNA from dead cells. J Microbiol Methods 2006; 67:310–320 [CrossRef][PubMed]
    [Google Scholar]
  16. Pan H, Zhang Y, He G-X, Katagori N, Chen H. A comparison of conventional methods for the quantification of bacterial cells after exposure to metal oxide nanoparticles. BMC Microbiol 2014; 14:222 [CrossRef][PubMed]
    [Google Scholar]
  17. de Boer FJ, Gieteling E, van Egmond-Kreileman H, Moshaver B, van der Leur SJCM et al. Accurate and fast urinalysis in febrile patients by flow cytometry. Infect Dis 2017; 49:380–387 [CrossRef][PubMed]
    [Google Scholar]
  18. Conkar S, Mir S. Urine flow cytometry in the diagnosis of urinary tract infection. Indian J Pediatr 2018; 85:995–999 [CrossRef][PubMed]
    [Google Scholar]
  19. Habtewold T, Duchateau L, Christophides GK. Flow cytometry analysis of the microbiota associated with the midguts of vector mosquitoes. Parasit Vectors 2016; 9:167 [CrossRef][PubMed]
    [Google Scholar]
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