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Clinical Research in Animal Science

Synergy Test for Antibacterial Activity: Towards the Research for a Consensus between the Fractional Inhibitory Concentration (Checkboard Method) and the Increase in Fold Area (Disc Diffusion Method)

Mbarga Manga Joseph Arsene*

Department of Microbiology and Virology, Medical Institute, People Friendship University of Russia, Moscow, Russia

*Corresponding author: Mbarga Manga Joseph Arsene, Department of Microbiology and Virology, Medical Institute, People Friendship University of Russia, Moscow, Russia

Submission: July 30, 2021;Published: August 04, 2021

Volume1 Issue4
August, 2021


Antibiotic resistance is a topical problem for both humans and animals and has been the subject of special monitoring for two decades. Several recent studies, including ours, have shown that this phenomenon is accentuated by the transfer of certain genetic elements and cross resistance acquisition, the latter or both resulting from the misuse of these antimicrobial drugs [1-3]. A more careful use of antimicrobials, the search for new antibacterial compounds (including probiotics and phages) are the most recommended alternatives to overcome this situation [4,5]. However, tests for modulations of antimicrobial activity can also play a major role. The main goal of synergy studies is to assess whether substances with antibacterial properties can improve the effectiveness of existing antimicrobials or give them a second life against resistant germs. Moreover, recent studies have demonstrated the ability of silver nanoparticles [5] and extracts of certain plants [6] to boost the effectiveness of certain antibiotics. such as ampicillin, benzylpenicillin, cefazolin, ciprofloxacin, nitrofurantoin, and kanamycin. Yet, from these studies we found that there was a serious problem with the interpretation of the results when using the disk method with determination of the increase in fold area. Indeed, the use of this method firstly requires the determination of the diameter of inhibition of the antibiotic alone; follow by the determination of the combination of antibiotic + modulating substance (MS) or extract. Finally, the calculation of the increase in fold area by the formula [7]:

A1 = Y2−X2/X2

Where, “A” is the increase in fold area, “Y” the zone of inhibition for extract + antibiotic and “X” is the inhibition zone of antibiotic alone.

This disc method has the following drawbacks:

1) It does not take into account the diameter of inhibition of the MS.

2) Variations in the initial inhibition diameter mislead the results. Because if we refer to this formula, the small variations of the inhibition diameters will be interpreted (using the increase in fold area) as being very important for the initial inhibition diameters small compared to the same variations for larger inhibition diameters. big.

3) It is difficult to come out with the significance scales of the effect despite the calculation of the increase in fold area and even if it were done, this classification would still have to be dependent on the diameter ranges.

To circumvent these drawbacks, some authors who have used this method simply assumed that synergy existed when there was an increase of more than 4mm [8]. in the diameter of inhibition while others preferred to represent the results as histogram or tables using raw data. However, unlike modulation by the disc diffusion method, the checkboard method considered both minimum inhibitory concentrations of the two substances being tested. In this method, the following formula is used: FIC=FICA+FICB, with:

FICA = MIC'A/ MICA and FICB = MIC'B/ MICB ; where FIC is the fractional inhibitory concentration, FIC A and FIC B are the FICs of each compound, MIC A and MIC B represent de MIC before the combination and MIC’A and MIC’B are the MIC of the same compounds after the combination [9,10].

The FIC index is interpreted as follows: FIC ≤0.5, synergy; 0.5 ≤FIC ≤1, addition of effects; 1≤ FIC≤4, indifference and for FIC> 4, Antagonism. In trying to highlight these two methods, for modulation by diffusion on disc, it would therefore be adequate for a better appreciation of the results, to consider a fourth variable representing the diameter of initial inhibition of the modulating substance. Thus, just as with the FIC, we could thus define the A1 and the A2 (respectively representing the increase in fold area of each of the two substances tested) in order to

A1 = Y−X/X and, A1 = Y−Z/Z , then finally calculate A=A1+A2.

Consequently, several scenarios emerge for the interpretation of the results:

A. If A1 or A2 < 0 and A1 + A2> 0, there is antagonism, and this antagonism is caused by one of the two substances.

B. If A1 and A2<0 the two substances are categorically antagonistic.

C. If A1 and A2>0, there may be additional effect or synergy.

This last case is the most interesting and necessarily requires laboratory tests to assess from what positive value of “A” there would be a significant synergistic effect in correlation with other existing methods. Hence, the proposed approach has the advantage of considering the two substances used and even leaves place for the combination of more than 2 other substances. Additionally, this new approach of interpretation makes it possible to reduce the deviations of the values of “A” when facing same variations between the high inhibition diameters compared to the low ones.

Ultimately, in-depth studies are required to confirm or refute the hypothesis we describe here. In addition, though this hypothesis better describes the synergistic effect between 2 tested substances, further investigations would also be needed to establish the intervals and degrees of significance when there is synergy between the two tested substances.


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  2. Mbarga MJA, Podoprigora IV, Volina EG, Ermolaev AV, Smolyakova LA (2021) Evaluation of changes induced in the probiotic Escherichia coli M17 following recurrent exposure to antimicrobials. Journal of Pharmaceutical Research International 33(29B): 158-167.
  3. Mbarga MM, Viktorovna PI, Grigorievna VE, Davares AK, Sergeevna DM, et al. (2021) Prolonged exposure to antimicrobials induces changes in susceptibility to antibiotics, biofilm formation and pathogenicity in staphylococcus aureus. Journal of Pharmaceutical Research International 33(34B): 140-151.
  4. Mbarga MJA, Davares AK, Andreevna SL, Vladimirovich EA, Carime BZ, et al. (2021) The use of probiotics in animal feeding for safe production and as potential alternatives to antibiotics. Vet World 14(2): 319-328.
  5. Joseph AMM, Podoprigora IV, Senyagin AN (2020) Silver nanoparticles enhance the effectiveness of antibiotics. FEBS Open Bio 11: 2­42.
  6. Manga MMJ, Viktorovna PI, Davares AKL, Esther N, Nikolaevich SA (2021) Urinary tract infections: Virulence factors, resistance to antibiotics, and management of uropathogenic bacteria with medicinal plants-A review. Journal of Applied Pharmaceutical Science 11(07): 001-012.
  7. Jain A, Ahmad F, Gola D, Malik A, Chauhan N, et al. (2020) Multi dye degradation and antibacterial potential of Papaya leaf derived silver nanoparticles. Environmental Nanotechnology, Monitoring & Management 14: 100337.
  8. Rolta R, Sharma A, Kumar V, Sourirajan A, Baumler DJ, et al. (2018) Methanolic extracts of the rhizome of emodi act as bioenhancer of antibiotics against bacteria and fungi and antioxidant potential. Medicinal Plant Research 8(9).
  9. Arsene MMJ, Zangue DSC, Ngoune TL, Nyasha K, Louis K (2021) Antagonistic effects of raffia sap with probiotics against pathogenic microorganisms. Foods and Raw materials 9(1): 24-31.
  10. Manga MM, Podoprigora IV, Davares AK, Razan M, Das MS, et al. (2021) Antibacterial activity of grapefruit peel extracts and green-synthesized silver nanoparticles. Vet World 14(5): 1330-1341.

© 2021 Mbarga Manga Joseph Arsene. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and build upon your work non-commercially.

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