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In Silico Drug Design of Biofilm Inhibitors of Staphylococcus epidermidis

by Al-mulla, Aymen Faraoun, MS


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Minimum binding
energy= -5.444

Figure 4.17 Thymol docking results


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4.2 Identification of Bacterial Isolates:
In this study ninety six bacterial isolates were collected from wounds ,ear
swaps and urine samples. Eighty seven (90.63%) were identified as
Staphylococci by a light microscope with the Gram stain technique. Sixty
five (67.7%) isolates were positive for biochemical tests of S.epidermidis
identification. All of them were coagulase negative, catalase positive,
sensitive to novobiocin and unable to ferment mannitol (Figure 4.18 A and
B) (Christensen et al., 1982).

A B

Figure 4.18 Antibiotic Sensitivity and Biochemical tests A- Red circle represent
novobiocin disc on muller Hinton media with inhibition zone (30 mm) for isolate No.
87 B- Mannitol salt agar were isolates No. 24,25,29 didn’t ferment mannitol and its
color remain pink,while isolate No.28 fermented it and the medium color turned to
yellow.


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4.3 Biofilm Producer S.epidermidis:
Sixty five S.epidermidis isolates were further investigated for biofilm
production. There are various methods to detect biofilm production like the
Tissue Culture Plate (TCP), the Tube method (TM), the Congo Red Agar
method (CRA), bioluminescent assay, piezoelectric sensors, and
fluorescent microscopic examination (Donlan et al., 2001; Aparna and
Yadav, 2008; Zufferey et al., 1988). In this study, the TM, the CRA and
the TCP methods were used as differential methods for biofilm producers.
The results of these methods as shown in (Table 4.2) demonstrate
variations when compared with each other.

Table 4.2 Results of biofilm producing isolates according to Tube method(TM) ,
Congo Red Agar method(CRA) and Tissue Culture Plate method(TCP).

No. of Isolates TM CRA TCP
+ - + - + -

65 9 56 21 44 8 57


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Control

Biofilm production with TM (Figure 4.19) was positive for nine isolates
(isolates no. 7,29,56,58,61,62,82,85,87). The rest, however, were either
weak or non-producers.

Figure 4.19 Biofilm detection using TM. The picture on right
represent two isolates, +ve and ve biofilm producers.
+ve -ve

The other method used for biofilm detection was the CRA, as shown in
(Figure 4.20), where the results were positive for twenty one isolates
(isolates no. 2,7,24,25,28,32,33,38,47,52,55
,56,58,60,61,62,69,70,81,82,86). The rest were negative producers,
however.

+ve -ve
Figure 4.20 Biofilm detection using CRA method. The picture on right represents non biofilm
producer S. epidermidis, while the picture on left represents two strains +ve and ve producers.


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The last method for biofilm detection was the TCP (Figure 4.21). This is a
quantitative method where (OD) of biofilm in the bottom of the culture
wells was determined by the ELISA autoreader. If the OD in the wells
exceeded 0.240, then it was classified as a strong producer. Strains whose
maximal OD was greater than 0.120 but less than or equal to 0.240 were
classified as weak producers. Values below 0.120 OD represent nonproducer
strains (Christensen et al., 1985).

A B

C D
Figure 4.21 Biofilm detection by TCP method. The picture on right represent biofilm stained at
the bottom of the wells. A: strong producer, B: weak producer, C : non producer and D: control

Statistical analysis of results

Eight isolates were strong biofilm producers (isolates no.
7,29,56,58,61,62,82,87). Isolate no. 85 was a weak producer, while the rest
were non-biofilm producers (Table 4.3).


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Table 4.3 Biofilm producing strains with their OD

Isolate No. OD Biofilm Production
56 4.0 strong
58 3.42 strong
62 3.02 strong
29 2.81 strong
7 1.17 strong
82 0.62 strong
87 0.6 strong
61 0.54 strong
85 0.23 weak

The TCP method was considered the gold-standard for this study
(because it is the only quantitative method) and compared with data from
the TM and CRA methods. Parameters, like sensitivity, specificity and
accuracy, were calculated.
True positives were biofilm producers by the TCP, TM and CRA method.
False positives were biofilm producers by the TM and CRA method and
not by the TCP method. False negatives were the isolates which were nonbiofilm
producers by the TM and CRA but were producing biofilm by the
TCP method. True negatives are those which were non biofilm producers
by all the three methods (Hassan et al., 2011).
The results shown in (Table 4.4) represent high sensitivity, specificity and
accuracy for TM and lower values for CRA method.


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Table 4.4 Statistical analysis values for TM and CRA method
Method Sensitivity Specificity Accuracy

TM 100% 98.25% 98.46%
CRA 75% 73.68% 73.85

The results above clearly show that the TM and TCP methods are more
accurate and reliable for biofilm detection. The fact that the CRA method
is not very accurate is being increasingly reported (Khudhur, 2013). The
congo red (CR) is a planar, hydrophobic, diazo dye which binds to lipids,
lipoproteins and to a broad range of other macromolecules (Gerard et al.,
1999). The dye interacts with the outer membranes and outer membrane
proteins (David et al., 2005).
It also binds to amyloid like fibers which have been recently detected and
isolated from S. epidermidis cultures and named as phenol soluble
modulines (PSMs) (Cogen et al., 2010). This ability to bind wide range of
macromolecules on the bacterial surface makes the CRA method less
accurate for biofilm detection.
On the other hand, the TCP and TM depend mainly on the slime
production and adhesion on solid surfaces. Primary adhesion between
bacteria and abiotic surfaces is generally mediated by nonspecific (e.g.,
hydrophobic) interactions, whereas adhesion to living tissues is
accomplished through specific molecular (lectin, ligand, or adhesin)
docking mechanisms (Carpentier and Cerf, 1993). First, the organism must
be brought into close approximation of the surface, propelled either
randomly (for example , by a stream of fluid flowing over a surface) or in
a directed fashion via chemotaxis and motility. Once the organism reaches
critical proximity to a surface (usually 1 nm), the final determination of


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adhesion depends on the net sum of attractive or repulsive forces generated
between the two surfaces. These forces include electrostatic , hydrophobic
interactions, steric hindrance, van der Waals forces, and hydrodynamic
forces (Carpentier and Cerf, 1993; Yuehuei et al., 2000).
Electrostatic interactions tend to favor repulsion, because most bacteria
and inert surfaces are negatively charged (except for slime producers
where cell surface became cationic). Hydrophobic interactions probably
have greater influence on the outcome of primary adhesion (Carpentier and
Cerf, 1993). Wang et al. demonstrated that primary adhesion of S
epidermidis to polyethylene disks was enhanced in the presence of surfaceactivated
platelets and reduced by adsorbed plasma proteins relative to
uncoated polyethylene (Wang et al., 1993).
Even though the principle of biofilm detection by these methods
(TCP,TM) depends on a variety of conditions, they remain better and more
accurate than CRA for biofilm detection.
For these reasons, the TM and TCP methods were used to select the best
two strains producing biofilm (isolates No. 56, 58) to be used in antibiofilm
activity experiments.

4.4 Bacterial Growth Curve:
Growth curves have been conducted to investigate the stage/point for
biofilm production and find out the effect of QS which could lead to the
formation of biofilm.
The two most biofilm producing isolates were selected to estimate the
growth curve for the bacterium and were compared with a non-biofilm
producing isolate.
Isolate No. 56 growth curves are shown in the figures below:


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Log
cfu/ml
7.5

7

6.5

6

5.5

5

4.5

0 5 10 15 20 25 30
Time (hr)

Figure 4.22 Growth curve for isolate No. 56 by using Viable Count

Figure 4.23 Growth curve for isolate No. 56 by using OD


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Figure 4.24 Slime production for isolate No. 56

Figure 4.25 Linear regression for Viable Count and OD for isolate No.56

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