Faculty of Science

CANNABIS EXTRACTS: A NOVEL APPROACH AGAINST MULTIDRUG-RESISTANT
BIOFILMS
2022 | KEILIN RUSSEL CHAD GORMAN

B.Sc. HONOURS THESIS - BIOLOGY

CANNABIS EXTRACTS: A NOVEL APPROACH AGAINST MULTIDRUGRESISTANT BIOFILMS
by
KEILIN RUSSEL CHAD GORMAN

A THESIS SUBMITTED IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF

BACHELOR OF SCIENCE (HONS.)
in the
DEPARTMENT OF BIOLOGICAL SCIENCES
(GENERAL BIOLOGY)

This thesis has been accepted as conforming to the required standards by:
Dr. Naowarat Cheeptham (Ph.D.), Thesis Supervisor, Dept. Biological Sciences
Dr. Joanna Urban (Ph.D.), Co-Supervisor, Dept. Biological Sciences
Dr. Natasha Ramroop-Singh (Ph.D.), Co-Supervisor, Dept. Biological Sciences
Dr. Eric Bottos (Ph.D.), External Examiner, Dept. Biological Sciences

Dated this 6th day of May 2022, in Kamloops, British Columbia, Canada
© Keilin Russel Chad Gorman, 2022

ABSTRACT
Multidrug-resistant biofilms present a severe global health crisis by combining the natural
resistance of the biofilm structure with the acquired resistance from genetic advantage. Cannabis
extracts offer a novel source of potential antimicrobial agents that can be used to treat infection.
Through the first stage of the present research, the protocol for culturing nine biofilm-producing
species was developed, and through the second stage of the research, a variety of terpenes and
cannabinoids isolated form Cannabis sativa were screened against Gram-positive and Gramnegative bacteria using an MBEC assay. Cannabidiol, tetrahydrocannabinol, and cannabigerol all
exhibited antibiofilm activity against five species of staphylococcal bacteria and were effective
against both multidrug-resistant and non-resistant strains. This work has established the research
principles required to focus future studies on combination assays to determine the synergistic
effects of cannabinoids and terpenes on bacteria which will increase the availability of novel
antimicrobials.

Thesis Supervisor: Professor Naowarat Cheeptham

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ACKNOWLEDGMENTS
I would like to first and foremost thank Dr. Naowarat Cheeptham for helping me develop
my project, answering my questions, and teaching me how to be a better researcher. Her expertise,
teaching philosophy, and support will be something I remember as I continue my journey as a
student outside of Thompson Rivers University. I would also like to thank Dr. Joanna Urban for
helping me find a focus for my research and being a source of knowledge throughout my project.
I am grateful to Dr. Natasha Ramroop-Singh and Dr. Eric Bottos for taking the time to read and
provide feedback on my thesis. I appreciate all the help from Dr. Mateen Shaikh with my statistics
and Dr. Nancy Flood for connecting me with him. My sincere appreciation goes to the TRU
UREAP for starting my research journey and to our collaborators at Avicanna who provided me
with the cannabis products and a profound insight into doing research with them. Kathy Baethke
has been instrumental in teaching me about all the equipment and has helped me gain confidence
in the lab. To Dr. Rehan and the microbiology lab at the Royal Inland Hospital, thank you for
providing me with the MDR bacteria and corresponding antibiograms. Lastly, Marissa Yoneda has
been an indispensable partner on this project. Not only has she assisted me directly with the MBEC
assays, but she has also helped me overcome our mistakes and celebrate our success as researchers.

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TABLE OF CONTENTS
ABSTRACT.................................................................................................................................... ii
ACKNOWLEDGMENTS ............................................................................................................. iii
LIST OF FIGURES ........................................................................................................................ v
LIST OF TABLES ......................................................................................................................... vi
LIST OF ABBREVIATIONS ....................................................................................................... vii
INTRODUCTION .......................................................................................................................... 1
Biofilms ..................................................................................................................................... 1
Multidrug-Resistant Bacteria as Pathogens .............................................................................. 3
Gram-Negative Bacteria ....................................................................................................... 3
Gram-Positive Bacteria ......................................................................................................... 4
Natural Metabolites as Antimicrobial Agents ........................................................................... 5
Cannabis Extracts ...................................................................................................................... 5
Objectives.................................................................................................................................. 7
MATERIALS AND METHODS.................................................................................................... 8
Characteristics and Collection of Multidrug-Resistant Bacteria............................................... 8
Antibiotic Stock Solution Preparation ...................................................................................... 9
Inoculum Preparation for Biofilm Growth.............................................................................. 10
Biofilm Growth Conditions .................................................................................................... 11
Preparation of Universal Neutralizer ...................................................................................... 13
Biofilm Growth Check ............................................................................................................ 14
Preparation of the Antimicrobial Challenge Plate .................................................................. 15
Antimicrobial Challenge and Biofilm Recovery .................................................................... 17
Determining the Minimum Inhibitory Concentration ............................................................. 18
Determining the Minimum Biofilm Eradication Concentration ............................................. 18
Statistical Analyses ................................................................................................................. 19
RESULTS ..................................................................................................................................... 19
Biofilm Growth Results .......................................................................................................... 19
Minimum Inhibitory Concentration Results ........................................................................... 21
Minimum Biofilm Eradication Results ................................................................................... 26

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Comparing MICs to MBECs Across Cannabinoids and Level of Susceptibility ................... 29
DISCUSSION ............................................................................................................................... 30
CONCLUSIONS AND FUTURE WORK ................................................................................... 34
LITERATURE CITED ................................................................................................................. 36
APPENDIX A – ANTIBIOGRAMS ............................................................................................ 40
APPENDIX B – DOSE RESPONSE CURVES ........................................................................... 45
APPENDIX C – BIOFILM GROWTH CONDITION RESULTS............................................... 46

LIST OF FIGURES
Figure 1. A S. aureus biofilm on the surface of an indwelling catheter that was removed from a
patient (Monroe 2007). ............................................................................................................. 2
Figure 2. Chemical structures of cannabinoids. (Top right, THC; Top left, CBD; Bottom, CBG) 6
Figure 3. An example of the multidrug-resistant Pseudomonas aeruginosa provided by the Royal
Inland Hospital after isolating it from a patient. ....................................................................... 8
Figure 4. The procedure for growing biofilms from clinical isolates or cryogenic stocks and
testing the anti-biofilm effects of cannabinoids. ..................................................................... 10
Figure 5. Examples of the first subcultures and streaking for isolated colonies (Left to right:
MDR P. aeruginosa, MDR MRSA, MDR E. coli). ................................................................ 11
Figure 6. The arrangement of the incubator used to grow biofilms including two beakers of
water, a hygrometer/thermometer, and the MBEC plate attached to the base of the incubator
with tape. ................................................................................................................................. 12
Figure 7. The organization of the MBEC plate for growing biofilms. Note: green, inoculated
broth; blue, sterile DI water. ................................................................................................... 13
Figure 8. A peg with biofilm growth. The peg is submerged to the orange line for growth in TSB
and submerged to the blue line for the challenge.................................................................... 14
Figure 9. The layout of the challenge plate with a two-fold concentration gradient of
cannabinoids in μg/mL in columns 1 to 9 and an array of control wells in columns 10 and 11.
Note: +, positive antibiotic control; -, negative growth control; BGC, biofilm growth ......... 16
Figure 10. The sonication apparatus used to ensure there was appropriate contact between the
water and the MBEC plate. ..................................................................................................... 17
Figure 11. The average logarithm of the initial inoculum density used to inoculate a biofilm plate
and the corresponding average logarithm of the biofilm density after incubation for nine
species of bacteria. Note: Error bars represent one standard deviation from the mean. ......... 21
Figure 12. The visual turbidity results from screening terpenes and cannabinoids against MRSA
biofilms where clear wells are evidence of inhibited growth. ................................................ 22
Figure 13. The visual turbidity results from screening CBD against MDR E. coli (EC), MDR P.
aeruginosa (PA), and MDR MRSA biofilms where clear wells are evidence of inhibited
growth. .................................................................................................................................... 23
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Figure 14. The MICs of CBD, THC, and CBG against five species of Gram-positive bacteria. . 24
Figure 15. The average MICs of CBD, THC, and CBG against Gram-positive bacteria (n=5).
Note: Error bars represent one standard deviation from the mean. ........................................ 25
Figure 16. The MBECs of CBD, THC, and CBG against 4 species of Gram-positive bacteria. . 27
Figure 17. The average MBECs of CBD, THC, and CBG against Gram-positive bacteria (n=4).
Note: error bars represent one standard deviation from the mean. ......................................... 28
Figure 18. The antimicrobial agent dose response curves for five species of Gram-positive
bacteria based on viable cell count. ........................................................................................ 45
Figure 19. The antimicrobial agent dose response curves for five species of Gram-positive
bacteria based on turbidimetry. ............................................................................................... 45
Figure 20. Examples of biofilms grown in TSB and stained with crystal violet (Top left: sterile;
Bottom left: MDR E. coli; Top right: MDR P. aeruginosa; Bottom right: MDR MRSA). ... 47

LIST OF TABLES
Table 1. The average optical density at 625 nm, concentration of viable cells in the initial culture,
concentration of viable cells in the biofilm after growth, and number of growth trials per
bacteria species. ...................................................................................................................... 20
Table 2. The pre-challenge biofilm densities for 5 species of Gram-positive bacteria and the
MICs of CBD, THC, and CBG against each species. ............................................................. 24
Table 3. Two-way ANOVA of the viable cell counts by species, cannabinoid concentration, and
the combination of these variables. ......................................................................................... 26
Table 4. The pre-challenge biofilm densities for 5 species of Gram-positive bacteria and the
MBECs of CBD, THC, and CBG against each species. ......................................................... 27
Table 5. Two-way ANOVA of the viable cell counts by species, cannabinoid concentration, and
the combination of these variables. ......................................................................................... 28
Table 6. Paired two-sample t-test comparing the mean MBECs and MICs for each cannabinoid.
(n=4) ........................................................................................................................................ 29
Table 7. Paired two-sample t-test comparing the mean MICs and MBECS between MRAS and S.
aureus. (n=3) ........................................................................................................................... 30

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LIST OF ABBREVIATIONS
Abbreviation
CBD
CBG
CFU
DMSO
EPS
MBEC
MDR
MIC
MRSA
PBS
THC
TSB

Meaning
Cannabidiol
Cannabigerol
Colony forming units
Dimethyl sulfoxide
Extracellular polymeric substances
Minimum biofilm eradication concentration
Multidrug-resistant
Minimum inhibitory concentration
Methicillin-resistant S. aureus
Phosphate buffered saline
Tetrahydrocannabinol
Tryptone soya broth

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INTRODUCTION
Biofilms

A biofilm is a microbial community of cells attached via an extracellular polymeric matrix
that enhances the survival and virulence of disease-causing bacteria (Lister and Horswill 2014).
Although the components of a biofilm matrix depend on the strain of bacteria and the local growth
conditions, they commonly contain host factors, polysaccharides, proteins, and extracellular DNA
(Montanaro et al. 2011; Cue et al. 2012; Foster et al. 2014). Biofilm growth occurs in three distinct
steps, and the steps are consistent across different species (Jamal et al. 2018). To begin, bacteria
attach to an inorganic or organic surface using their appendages (e.g., pili or flagella) or through
physical forces (e.g., electrostatic interactions) and reproduce on the surface to create a
microcolony. Then, bacteria use quorum sensing to begin creating extracellular polymeric
substances (EPS) to form the biofilm matrix with channels throughout the matrix to distribute
nutrients and remove waste from the biofilm. Lastly, at maturation, some bacteria from the biofilm
begin to disperse to colonize other parts of the environment. This detachment step makes biofilms
especially dangerous because once the biofilm is established in the body, individual cells can move
to other parts of the body creating a more widespread infection or sepsis (Costerton et al. 1999).
To completely eradicate a biofilm, it is necessary to first destroy the EPS which releases the
bacteria as planktonic cells, and then use an antibiotic to kill the planktonic bacteria (Muhammad
et al. 2020). As such, combinations of drugs where one is used to destroy the biofilm and another
to kill the bacteria, are often used to treat persisting biofilm infections (Farha et al. 2020).

All bacteria are assumed to be capable of producing biofilms, but the ability varies
depending on the environmental conditions for growth and strain-specific differences that

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complicate growing biofilms in vitro (López et al. 2010). Regarding biofilm-associated infections
in humans, bacteria in the genus staphylococcus account for approximately two-thirds of infections
on indwelling medical devices (Khatoon et al. 2018). In particular, the most reported Grampositive and Gram-negative bacteria that cause biofilm infections are S. aureus and P. aeruginosa,
respectively (Khatoon et al. 2018).

Figure 1. A S. aureus biofilm on the surface of an indwelling catheter that was removed from a
patient (Monroe 2007).
Although previous screening methods for antibiotics have focused on targeting planktonic
bacteria, antibiotics that successfully destroy planktonic bacteria are frequently ineffective in
bacteria that have formed a biofilm (Ceri et al. 2001). Illustrating the drastic difference in antibiotic
susceptibility between planktonic and biofilm populations, Ceri et al. (1999) determined that the
minimum biofilm eradication concentration (MBEC) was 100 to 1000 times higher than the
minimal inhibitory concentration of planktonic populations for penicillin, oxacillin, cefazolin,
ciprofloxacin, clindamycin, and vancomycin. The reason for the enhanced resistance in biofilms
lies in their unique structure and physiology. Biofilms are multi-layered structures which reduces
the ability of antibiotics to penetrate to the base of the biofilm where cells can persist uninhibited

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(Khatoon et al. 2018). Likewise, the matrix can be packed with efflux pumps which remove the
antibiotics even if they manage to penetrate deeper layers (Khatoon et al. 2018). Considering the
severe health risks associated with biofilm growth mentioned above, the MBEC assay is an
efficient and relevant technique to test novel antibiotics and other biofilm inhibitors.

Multidrug-Resistant Bacteria as Pathogens
Gram-Negative Bacteria

Pseudomonas aeruginosa is a Gram-negative opportunistic pathogen that infects a host
whose immune system is already compromised (Mulcahy et al. 2014). Due to its flexible
metabolism and role in disease, it is a species of interest whose biofilm is frequently used to
develop biofilm inhibitors. Infections with P. aeruginosa are common in patients with cystic
fibrosis and burns or chronic wounds with sampling showing that its biofilm growth occurs deep
in wounds making it more difficult to treat (Mulcahy et al. 2014). Characterization of the P.
aeruginosa genome showed that it expresses drug-resistant genes including the genes for multidrug resistant pumps, beta-lactam antibiotic resistance, and aminoglycoside antibiotic resistance
(Poole 2001; Vahdani et al. 2012).

Of particular interest, P. aeruginosa biofilm can grow on inorganic surfaces or equipment
in hospitals and on implanted biomaterials such as catheters and ventilator tubes (Peleg and Hooper
2010; Ganderton et al. 1992). On implanted biomaterials, the biofilm prevents neutrophil and
macrophage activity from eliminating the infection and protects the bacterial population from
antibiotics (Leid et al. 2005). P. aeruginosa infections occurring in American hospitals infect at
least 2 million patients a year and with at least 90,000 of those infections being fatal (Mulcahy et
al. 2014). Between 1993 and 2002, rates of multi-drug resistance in P. aeruginosa isolated from

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ICU patients increased by 10% with 64 antibiotic-resistant genes being well-conserved between
the resistant strains (Obritsch et al. 2004; Hwang and Yoon, 2019).

As a model organism, Escherichia coli has been studied extensively in the context of
infection and disease. E. coli is also a Gram-negative bacterium in which certain strains produce
harmful toxins associated with Crohn’s disease, urinary tract infections (UTI), and meningitis
(Sharma et al. 2016). Since E. coli readily forms biofilms, it is frequently responsible for catheterassociated urinary tract infections which is one of the most common hospital-acquired infections
(Reisner et al. 2014). Of particular concern, the processing of animals for food has created an
abundant reservoir of resistant E. coli that pose a risk of spilling over into humans and hospitals.
Resistance to β-lactam antibiotics has been observed in approximately 20% of E. coli samples
from animal processing plants with high rates of horizontal gene transmission for resistance genes
across strains (Gregova and Kmet 2020).

Gram-Positive Bacteria

Like P. aeruginosa and E. coli, Staphylococcus aureus represents a significant health risk
to patients in hospitals. These Gram-positive bacteria can live commensally in the human nasal
cavity but impose health risks when infection and biofilm growth occur on bone, heart valves,
catheters, pacemakers, and prosthetic joints (Lister and Horswill 2014). Human proteins eventually
coat implanted biomaterials creating an ideal surface for S. aureus biofilm growth since proteins
on the surface of the bacteria can bind to the host proteins (François et al. 1996; Cheung and
Fischetti 1990). Methicillin-resistant S. aureus (MRSA) is especially threatening, accounting for
25 to 50% of S. aureus hospital infections with high rates of mortality (Lakhundi and Zhang 2018).

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Natural Metabolites as Antimicrobial Agents
The vast majority of antibiotics are derived from natural products which are often more
active and have less side effects that synthetically derived alternatives (Mishra et al. 2020).
Phytochemicals are a broad class of biologically active metabolites from plants, many of which
have anti-biofilm effects. Although the mechanism of action of phytochemicals depends on the
specific compound, general anti-biofilm mechanisms include disrupting the cell membrane,
preventing cellular adhesion, sequestering of essential proteins through binding, and inhibiting
quorum sensing (Lu et al. 2019).
Bacterial metabolites are also a source of anti-biofilm agents, especially those that degrade
the EPS. For example, S. epidermidis can produce serine proteases that degrade S. aureus surface
proteins (Sugimoto et al. 2013) and Actinobacillus actinomycetemcomitans can release beta-Nacetylglucosaminidase that degrade S. epidermidis biofilms (Mishra et al. 2020). The natural
environment offers an expansive source of antimicrobial agents whether it be from plants, bacteria,
or inorganic materials. Understanding the purpose of these metabolites in nature can better inform
how we implement them in healthcare.

Cannabis Extracts

Cannabinoids are evolutionarily advantageous to the cannabis plant and provide several
defenses against abiotic factors. Cannabinoids are concentrated in trichomes located on the outside
of the leaves and flowers of the plant (Gülck and Moller 2020). If insects begin to eat the plant,
the trichomes can rupture which traps them in a viscous fluid preventing further herbivory (Gülck
and Moller 2020). The same process can occur if the plant is under heat stress where the
cannabinoid-rich fluid coats the leaves to prevent desiccation (Desaulniers et al. 2021). Likewise,

5

the structures of cannabinoids allow the absorption of UV-B light which reduces DNA damage
and cannabinoids play a role in the defense against infection in the cannabis plant (Desaulniers et
al. 2021; Gülck and Moller 2020).

In humans, the anticancer and anti-inflammatory effects of cannabis extracts are wellcharacterized and provide incentive to diversify the medical applications of Cannabis sativa
(Blaskovich et al. 2021). Current approaches focus on optimizing the antibacterial activity of
cannabis extracts to reduce the reliance on antibiotics and target multi-drug resistant bacteria which
are causing deaths that were once preventable. CBD can inhibit P. aeruginosa biofilm formation
by 70% and even remove preformed biofilms that persist when treated with only antibiotics (Di
Onofrio et al. 2019).

Figure 2. Chemical structures of cannabinoids. (Top right, THC; Top left, CBD; Bottom, CBG)
Both THC and CBD have minimum inhibitory concentrations of 1-5 μg/mL against
planktonic S. aureus, illustrating that these compounds have antimicrobial activity against both
Gram-positive and Gram-negative bacteria (Blaskovich et al. 2021). Although the precise
mechanism of action of cannabis extracts against biofilms is not well-understood, it is likely that

6

CBD alters the aggregation and spreading ability of bacteria by preventing vesicle release and thus,
eliminating communication within a community of cells (Blaskovich et al. 2021). Radiolabeled
macromolecular synthesis assays in S. aureus have also shown that CBD can inhibit protein, DNA,
RNA, and peptidoglycan synthesis processes (Blaskovich et al. 2021). In addition to being used to
treat bacterial infections directly, the synergistic properties of CBD for antibiotics are being
evaluated to increase the susceptibility of resistant bacteria to antibiotics (Di Onofrio et al. 2019).

Objectives
The first objective of this research was to determine if we could culture biofilms from a
diverse set of bacteria including Gram-positive and Gram-negative species, as well as multidrugresistant (MDR) and non-resistant strains. Following successful growth of biofilms and the
preliminary screening of specific cannabis extracts, the second objective was to determine the
minimum inhibitory concentration (MIC) and MBEC of CBD, THC, and CBG against a variety
of staphylococcal bacteria. This allowed us to make comparisons between the efficacy of
cannabinoids against planktonic versus biofilm bacteria and provide insight into the possible
mechanisms of action against the bacteria. By measuring the MBEC and MIC between MDR and
non-resistant strains, we determined if multidrug resistance in bacteria extends to CBD, THC, and
CBG or if MDR strains are just as susceptible to cannabinoids as their non-resistant counterparts.
Lastly, modelling of the antimicrobial dose response curves allowed us to compare the curves by
cannabinoid and by species providing an overall pattern of activity across variables. Since bacteria
are becoming increasingly resistant to multiple classes of existing antibiotics and fewer antibiotics
are being developed and approved, infections that were once treatable are becoming fatal (Baker
et al. 2018; Ventola 2015). Overall, we seek to evaluate the efficacy of using cannabis extracts as

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novel therapeutic agents against bacterial infection which will diversify our options for treating
patients and reduce the dependency of our healthcare system on currently existing antibiotics.
MATERIALS AND METHODS
Characteristics and Collection of Multidrug-Resistant Bacteria

The Royal Inland Hospital provided ten clinical strains of multi-drug resistant bacteria
representative of three different species including Escherichia coli, Pseudomonas aeruginosa, and
methicillin-resistant Staphylococcus aureus. Antibiograms for each strain were provided by the
hospital and are reported in the appendix. E. coli #1, P. aeruginosa #3, and MRSA #4 were chosen
to be subcultured on antibiotic-supplemented media to maintain selective pressure on the bacterial
community. Cryostocks of each strain were made by mixing 500 μL of 20% glycerol with 500 μL
broth culture in sterile cryovials to be stored at -80 °C. Laboratory strains of susceptible Grampositive and Gram-negative bacteria were also obtained. The Gram-positive bacteria included nonresistant Staphylococcus aureus, Staphylococcus intermedius, Staphylococcus epidermidis, and
Staphylococcus hycius. The Gram-negative bacteria included non-resistant Escherichia coli and
Klebsiella pneumoniae.

Figure 3. An example of the multidrug-resistant Pseudomonas aeruginosa provided by the Royal
Inland Hospital after isolating it from a patient.
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Antibiotic Stock Solution Preparation
A 0.02 g/mL (1000×) ciprofloxacin stock solution was prepared by mixing the antibiotic
with sterile deionized water (15 mΩ). Since antibiotics do not retain stability in the autoclave, the
solution was passed through a 0.22μm filter and stored at 4 °C for at most 2 weeks. Based on the
provided antibiograms, ciprofloxacin-supplemented agar plates were used to subculture E. coli #1,
P. aeruginosa #3, and MRSA #4, and these bacteria were subsequently used for antimicrobial
screening and for observing biofilm growth along with the susceptible laboratory strains. Although
ciprofloxacin is a broad-spectrum antibiotic that can be effective against both Gram-positive and
Gram-negative bacteria, its widespread availability is contributing to bacterial resistance (Sharma
et al. 2017).

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Inoculum Preparation for Biofilm Growth

The experimental procedure for growing the biofilms and screening the cannabis extracts was
adapted from the Innovotech MBEC Assay Procedural Manual 2.1 and is shown in Figure 4.

Figure 4. The procedure for growing biofilms from clinical isolates or cryogenic stocks and testing
the anti-biofilm effects of cannabinoids.
The first subcultures (shown in Figure 5) were obtained by streaking bacteria from the
clinical isolates onto nutrient agar and incubating the plates at 37 °C for 18-24 hours. These
subcultures can be stored at 4 °C for 14 days once sealed with Parafilm. After ensuring the purity
of the subculture through morphological observations of the colonies, a second subculture was
obtained by streaking isolated colonies from the first subculture onto nutrient agar. Likewise, these
plates were incubated at 37 °C for 18-24 hours. The second subculture was used to inoculate the
96-well MBEC Assay Biofilm Inoculator plate within 24 hours starting from the time the
subculture is removed from the incubator.
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Figure 5. Examples of the first subcultures and streaking for isolated colonies (Left to right: MDR
P. aeruginosa, MDR MRSA, MDR E. coli).
To prepare the liquid culture for inoculating the biofilm plate, isolated colonies from the
second subculture were emulsified in sterile deionized water in a sterile glass test tube. The
suspension was adjusted to an OD625 of 0.08-0.13 using water as a blank by adding more bacteria
or by diluting with more sterile water. This absorption is approximately equivalent to 1.5 × 10 8
CFU/mL (Innovotech 2019). Then, 34 μL of the suspension was added to 50 mL of sterile broth
dilute it to an approximate cell density of 105 CFU/mL. The exact cell density for each strain was
determined by performing a serial dilution of the broth and spot plating on nutrient agar plates. All
serial dilutions throughout the experimental procedure were performed by diluting 20 μL of
inoculum in 180 μL of sterile DI water and spot plating 20 μL of inoculum onto a Petri plate.

Biofilm Growth Conditions

The optimal biofilm growth conditions for the MDR bacteria were evaluated prior to this
study and the growth condition results are briefly reports in Appendix D. Biofilms were incubated

11

in TSB for 16 hours at 37 °C, 110 rpm, and 65% humidity. The arrangement of the humidified
incubator is shown in Figure 6.

Figure 6. The arrangement of the incubator used to grow biofilms including two beakers of water,
a hygrometer/thermometer, and the MBEC plate attached to the base of the incubator with tape.
A standard organization of the MBEC plate was created to grow biofilms for antimicrobial
screening. Using a multi-channel micropipette, 150 μL of liquid culture was added to each well of
columns 1 to 9; the wells in column 10, rows C to H; and the wells in column 11, rows F-H of a
96-well MBEC Assay Biofilm Inoculator plate, the plate was carefully covered with the peggedlid and parafilmed. The organization of the MBEC for growing biofilms is shown in Figure 7.

The wells in columns 10 and 11, rows A and B were not needed for the assay and were
only filled with water. The wells in column 11, rows C to E were used as sterile control wells in
the challenge plate and thus, could not be inoculated. Despite the attempt to reduce the evaporation
of media in wells by increasing the humidity of the incubator, we consistently observed reduced
volumes in column 12 so it was only ever filled with water and disregarded from being included
in the MBEC assay.

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Figure 7. The organization of the MBEC plate for growing biofilms. Note: green, inoculated broth;
blue, sterile DI water.

Preparation of Universal Neutralizer
Universal neutralizers are used to decrease the toxicity of the antimicrobial agents used in
the experiment to prevent any effects on the bacteria from carrying over after the challenge
(Innovotech 2019). To prepare the neutralizer, 2.00 g reduced L-glutathione, 1.00 g DL-cysteine,
and 1.00 g L-histidine were added to sterile deionized water to a total volume of 20 mL. This
solution was filter-sterilized with a 0.22 μm filter. Surfactant-supplemented TSB was also prepared
to help recover the biofilm removed from the sonicated pegs during the recovery step. 0.60 g of
saponin and 0.32 g of Tween-80 were added to 30 mL of TSB and the solution was adjusted to a
pH of approximately 7.0 at 25 °C with 2 M NaOH. 500 μL of the universal neutralizer was added
to 20 mL of the surfactant-supplemented TSB which was used to recover the biofilms.

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Biofilm Growth Check

After incubation and prior to antimicrobial challenge, a growth check was performed to
determine the biofilm density on the pegs. A rinse plate was prepared by filling each well of a 96well microtiter plate with 200 μL PBS. The pegged-lid of the MBEC plate was placed into the
microtiter plate for approximately 10 seconds to rinse any dispersed cells from the biofilms. This
is to ensure an accurate calculation of biofilm density since dispersed cells would contribute to the
value of CFU/mL even though they are not physically attached within the biofilm matrix. Then,
three pegs from column 11, rows F to H were removed from the lid with flame-sterilized pliers by
gripping at the base of the biofilm and taking caution to avoid disturbing the biofilm.

Approximate region to grip
the peg with pliers

150 μL

200 μL

Figure 8. A peg with biofilm growth. The peg is submerged to the orange line for growth in TSB
and submerged to the blue line for the challenge.
The pegs were transferred into 200 μL of the surfactant-supplemented universal neutralizer
recovery media in Eppendorf tubes. The plate was covered with a lid and the seam between the
plate and the lid was sealed with parafilm. The Eppendorf tubes were submerged in the basin of a
sonicator and were sonicated at 40 kHz for 30 minutes.

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The biofilm density for each species of bacteria was determined by performing a serial
dilution of the recovery media and spot plating. In a previous test, the pegs were sonicated at 40
kHz for either 30, 60, or 90 minutes to determine the elapsed time at which the most biofilm was
recovered. The recovery medium was spot plated after sonication to compare the sonication times
and there were only viable cells after 30 minutes of sonication. This suggests all of the cells were
killed at least after 60 minutes in the sonicator.

Preparation of the Antimicrobial Challenge Plate
The organization of the challenge plate was modified from the layout provided in the
MBEC Assay Procedural Manual 2.1 (Innovotech 2019). The cannabis extract stock solutions
were prepared by adding pure extracts to 1.0 mL of dimethyl sulfoxide (DMSO) and then adjusting
the concentrations of the solutions to 125 μg/mL. This was done by pipetting the appropriate
amount of the DMSO solution into enough TSB to fill the wells depending on how many columns
of each cannabis extract were being used for the challenge. DMSO has no inhibitory effect on S.
aureus at concentrations below 0.1% so the concentration was maintained below this threshold for
all assays (Yadav et al. 2015). Approximately 4 mL of cannabis extract solution is required for the
entire plate. All of the stock solutions were filter-sterilized with a 0.22 μm filter to prevent
contamination. A serial two-fold dilution gradient of each extract being tested was created in
columns 1 to 9 in order to determine the MBEC and MIC of the extracts. To set up the
concentration gradient, 200 μL of the 125 μg/mL cannabis extract solution was added to row A of
the plate and 100 μL of 125 μg/mL cannabis extract solution was added to both row B and C. Then,
100 μL of TSB was added to each well in columns 1 to 9, rows B to H. Starting in row C, the
contents of the wells were mixed by pipetting up and down with a multichannel pipette and then
100 μL was transferred from the wells in row C to the wells in row D. The mix-and-transfer process

15

was repeated in each row until reaching row H and pipette tips were discarded between each
transfer. Lastly, 100 μL of solution was discarded from row H before again adding 100 μL of TSB
to each well in columns 1 to 9, rows C to H. The volume of all of the wells was 200 μL to ensure
the entire surface area of the biofilm on the peg would be submerged. In general, columns 1 to 3
had CBD, columns 4 to 6 had THC, and columns 7 to 9 had CBG. Ciprofloxacin (0.02 g/mL) was
added in column 10, rows C to E, as a positive control for the trials with susceptible strains. TSB
was added to column 11, rows C to E as a sterility control to ensure there was no crosscontamination between wells. TSB was also added to column 10, rows F to H as a negative control
that was not exposed to treatment and was used to verify uninhibited growth after the challenge.

Figure 9. The layout of the challenge plate with a two-fold concentration gradient of cannabinoids
in μg/mL in columns 1 to 9 and an array of control wells in columns 10 and 11. Note: +, positive
antibiotic control; -, negative growth control; BGC, biofilm growth
The challenge plate was aseptically covered and left for 30 minutes at room temperature
and used within a day of being prepared. Before covering the challenge plate with the pegged-lid
and exposing the biofilms, the optical density of each well was measured using at automated plate

16

reader at 621 nm1. This was done to have a baseline to which the wells could be compared to after
the biofilms were incubated while exposed to the cannabinoids in the challenge plate.

Antimicrobial Challenge and Biofilm Recovery
After rinsing the pegs in PBS and removing the biofilm growth check pegs, the lid was
placed on the challenge plate, submerging the pegs in the solutions. The plate was placed in the
humidified incubator at 37 °C and 110 rpm for an exposure time of 16 hours. A recovery plate was
prepared by adding 200 μL of the surfactant-supplemented universal neutralizer recovery media
to each well of a 96-well microtiter plate. After the challenge, the lid was immediately transferred
to the recovery plate and left at room temperature for 30 minutes. Then, the plate was sonicated at
40 kHz for 30 minutes to dislodge the biofilms.

Figure 10. The sonication apparatus used to ensure there was appropriate contact between the
water and the MBEC plate.2

1

The optical density of the culture diluted to inoculate the MBEC plate was measured at 625 nm, however the
automated plate reader was set to 621 nm because that was the closest available filter.

2

The forceps were used to raise the wire basket to the correct height so that basin could be filled with water to
the correct level without submerging the recovery plate.

17

Determining the Minimum Inhibitory Concentration
After removing the pegged-lid from the challenge plate, it was aseptically covered with an
non-pegged lid and incubated again for 16 hours at 37 °C, 110 rpm, and 65% humidity. Following
the incubation time, the optical density of each well was measured again at 621 nm using an
automated plate reader. The absorbances of the wells in the challenge plate before the challenge
were measured and subtracted from these absorbances to determine the relative change in
absorbance at each concentration of the cannabinoids. Wells that either had no change or a negative
change in absorbance show evidence that the growth of the cells that dispersed from the biofilm
during exposure were inhibited.

Determining the Minimum Biofilm Eradication Concentration
To determine the minimum biofilm eradication concentration of the cannabinoids, the
viable cell count for each extract and each concentration was calculated. Following the recovery
of the biofilms, 100 μL of recovery medium from each well in columns 2, 5, and 7 and wells F to
H from column 10 were transferred from the recovery plate into Eppendorf tubes. The wells in
column 10 were not exposed to the cannabinoids and served as untreated control pegs which would
be compared to the treated pegs to calculate the Log10Reduction. Columns 2, 5 and 7 were single
replicates of the columns with CBD, THC, and CBG, respectively. Each 100 μL aliquot that was
transferred to the Eppendorf tubes was serially diluted and the resulting solutions were spot plated
to calculate the viable cell count at every concentration of cannabis extract.

18

Statistical Analyses
Statistical analyses were conducted using the programming language R and Microsoft
Excel. To ensure the data were normally distributed, the data were fitted to a Q-Q plot whereby
normally distributed data appears as a straight line. In R, multi-level linear regression ANOVAs
were used to compare the responses of the bacteria to the cannabinoids. A linear trendline was
fitted to the dose response curves and each combination of bacteria and cannabinoid was compared
to determine if there was variance in the data. In Excel, paired two-sample t-tests were completed
to compare the average MICs and MBECs of CBD, THC, and CBG, as well as to compare the
MICs and MBECs of the cannabinoids between MDR MRSA and non-resistant S. aureus.

RESULTS
Here we show the biofilm growth results for nine species of bacteria with species that are
Gram-positive, Gram-negative, MDR, and non-resistant. The visual turbidity results from the
preliminary screening of cannabis extracts against representative species of Gram-positive and
Gram-negative bacteria are displayed and the MICs and MBECs for CBD, THC, and CBG are also
reported against five species of Gram-positive bacteria. Comparisons between the susceptibility to
cannabinoids of biofilms versus planktonic bacteria are made, as well as comparisons between the
susceptibility to cannabinoids of MDR versus non-resistant strains.

Biofilm Growth Results
The optical density at 625 nm of the culture, which was then diluted to create the initial
cultures, corresponding viable cell count for the initial cultures used to inoculate the MBEC plates,
and viable cell count from the biofilms are shown in Table 1.

19

Table 1. The average optical density at 625 nm, concentration of viable cells in the initial culture,
concentration of viable cells in the biofilm after growth, and number of growth trials per bacteria
species.
Absorbance
(OD625)
K. pneumoniae
0.121
E. coli
0.096
MDR E. Coli
0.119
MDR P. aeruginosa
0.111
MDR MRSA
0.113
S. aureus
0.118
S. epidermidis
0.109
S. intermedius
0.110
S. hycius
0.118
Species

Initial Density
(CFU/mL)
3.5 × 104
9.0 × 104
1.1 × 105
2.3 × 105
1.3 × 105
8.0 × 104
6.0 × 104
4.6 × 104
6.2 × 104

Biofilm density
(CFU/mL)
3.5 × 104
8.5 × 105
6.8 × 105
1.7 × 107
1.6 × 106
4.6 × 106
8.0 × 106
1.1 × 106
3.2 × 106

Sample
size (n)
1
1
2
2
7
2
2
2
2

Briefly, the absorbance of the initial cultures ranged from 0.096 to 0.121 (M = 0.113) which
corresponded to a viable cell count with a range from 3.5 × 104 to 2.3 × 105 (M = 9.37 × 104)
CFU/mL. The most growth was observed in the non-resistant strain of E. coli with an increase of
5.391 × 107 CFU/mL from the initial culture to the biofilm. In contrast, the least growth was
observed in K. pneumoniae where the initial culture had the same number of viable cells as the
biofilm. Displayed in Figure 11, the initial inoculum and biofilm densities were log transformed
to show the increase in growth for the biofilms. In all cases except for K. pneumoniae, the biofilm
density was higher than the initial inoculum density. In general, the biofilm density increased 2fold compared to the initial density used to inoculate the MBEC plates; however, there was some
variability in the pattern of increased growth both within the species where biofilms were grown
multiple times and among the 9 species that were tested for growth.

20

10.00

9.00

Log of CFU/mL

8.00
7.00
6.00
5.00

4.00
3.00

Biofilm Density
Initial Inoculum Density

2.00
1.00
0.00

Figure 11. The average logarithm of the initial inoculum density used to inoculate a biofilm plate
and the corresponding average logarithm of the biofilm density after incubation for nine species
of bacteria. Note: Error bars represent one standard deviation from the mean.

Minimum Inhibitory Concentration Results
Pre-screening visual turbidity results were initially used to determine which cannabis
extracts against which bacteria should be further investigated in detail. MRSA biofilms with a cell
density of 4.5 × 106 CFU/mL were exposed to concentration gradients of terpenes, including
eugenol, β-carotene, carvacrol, α-pinene, and linalool, all of which showed no visible activity
against the biofilms. In the same plate, the biofilms were also exposed to cannabinoids, including
CBD, THC, and CBG, all of which did show activity against the biofilms. The results of this trial
are shown in Figure 12. Note that the cannabinoids and terpenes are not entirely clear either
contributing to the cloudiness seen in the first 2 wells for THC, CBD, and CBG.

21

CBG

CBD

THC

Eugenol

β-carotne

Carvacrol

α-pinene

Y Linalool

Figure 12. The visual turbidity results from screening terpenes and cannabinoids against MRSA
biofilms where clear wells are evidence of inhibited growth.

Next, to compare the activity of the cannabinoids against MDR Gram-positive and MDR
Gram-negative species, E. coli biofilms with a cell density of 1.2 × 106 CFU/mL, P. aeruginosa
biofilms with a cell density of 3.45 × 107 CFU/mL, and MRSA biofilms with a cell density of 3.25
× 104 CFU/mL were exposed to concentration gradients of CBD. As shown in Figure 13, the
cannabinoids had no visible activity against MDR E. coli or MDR P. aeruginosa, but again showed
activity against MDR MRSA.

22

EC

PA

MRSA

Figure 13. The visual turbidity results from screening CBD against MDR E. coli (EC), MDR P.
aeruginosa (PA), and MDR MRSA biofilms where clear wells are evidence of inhibited growth.

Based on these results, we decided to further characterize the effects of the cannabinoids,
CBD, THC, and CBG, against five species of staphylococcal Gram-positive bacteria, including
MDR MRSA and non-resistant S. aureus, S. intermedius, S. hycius, and S. epidermidis. Although
primarily interested in the MIC and MBEC values for each cannabinoid against each species, the
antimicrobial dose response curves used to determine the MICs and MBECs are provided in the
appendix for reference. Shown in Table 2, the MICs against the Gram-positive bacteria range from
3.91 μg/mL to 31.25 μg/mL for CBD, 7.81 μg/mL to 62.5 μg/mL for THC, and 3.91 μg/mL to
15.63 μg/mL for CBG. The MICs of each cannabinoid against each species are shown in Figure
14 for comparison.

23

Table 2. The pre-challenge biofilm densities for five species of Gram-positive bacteria and the
MICs of CBD, THC, and CBG against each species.
Pre-challenge
biofilm density
(CFU/mL)
2.6 × 105
2.3 × 106
8.5 × 103
1.8 × 106
4.5 × 105

Species
MDR MRSA
S. aureus
S. epidermidis
S. intermedius
S. hycius

CBD MIC
(μg/mL)

THC MIC
(μg/mL)

CBG MIC
(μg/mL)

3.91
7.81
3.91
31.25
3.91

31.25
62.5
31.25
15.63
7.81

3.91
15.63
3.91
15.63
7.81

70.0

Concentration (μg/mL)

60.0
50.0
40.0

MRSA
S. aureus

30.0

S. epidermidis
S. intermedius

20.0

S. hycius

10.0
0.0
CBD

THC

CBG

Type of Cannabinoid

Figure 14. The MICs of CBD, THC, and CBG against five species of Gram-positive bacteria.

Illustrating the overall trend in cannabinoid activity across the five species of bacteria using
turbidimetry, Figure 15 shows that THC seems to be least active and have the highest MIC (M =
29.69 μg/mL, SD = 20.96 μg/mL) against the bacteria, followed by CBD (M = 10.16 μg/mL, SD

24

= 11.91 μg/mL), and lastly, CBG which was the most active and had the lowest MIC (M = 9.38
μg/mL, SD = 5.93 μg/mL) against the bacteria. With that said, there is a high degree of variation
across the species of bacteria as indicated by the high standard deviation shown by the error bars
in Figure 15.
60.0

Concentration (μg/mL)

50.0
40.0
30.0
20.0
10.0
0.0
CBD

-10.0

THC

CBG

Type of Cannabinoid

Figure 15. The average MICs of CBD, THC, and CBG against Gram-positive bacteria (n=5).
Note: Error bars represent one standard deviation from the mean.

A multilevel linear regression model was applied to the bacteria species, cannabinoid type,
and cannabinoid concentration as independent variables and the logarithm of the change in
absorbance as the dependent variable. A two-way ANOVA was used to assess the variability of
the regressions across species, determine if the slopes of the dose response curves were non-zero
values, and if the regressions were consistent across each species-cannabinoid combination. The
statistical outputs from the two-way ANOVA are reported in Table 3.

25

Table 3. Two-way ANOVA of the viable cell counts by species, cannabinoid concentration, and
the combination of these variables.
Measure
Species
Cannabinoid
Species + cannabinoid

F-value
1.534
258.401
2.131

P-value
0.1918
< 2 × 10-16
0.0148

Based on these results, there does not appear to be a difference in the response to the
cannabinoids across species overall, however, there is a variation between the data for every
specific combination of species and cannabinoid. For the cannabinoid concentration measure, the
extremely low P-value indicates that the slopes of the absorbance antimicrobial dose response
curve are non-zero which confirms the obvious trend from the response curves whereby increasing
the concentration of cannabinoid decreases the viable cell count.

Minimum Biofilm Eradication Results
As another measure of the activity of cannabinoids against the bacteria, the minimum
biofilm eradication concentration provides a direct assessment of the efficacy of antimicrobials
against the biofilms. Shown in Table 4, the MBECs against the Gram-positive bacteria range from
1.95 μg/mL to 15.63 μg/mL for CBD, 3.91 μg/mL to 31.25 μg/mL for THC, and 3.91 μg/mL to
15.63 μg/mL for CBG. The MBECs of each cannabinoid against each species are compared in
Figure 16. The viable cell counts for S. epidermidis were excluded based on abnormalities in the
CBG dose response curve reflected in growth of the bacteria at concentrations higher than the
initial MBEC value. The biofilm density for S. epidermidis was also below the 104 to 106 range
ideal for antimicrobial susceptibility testing. There was also no MBEC value for THC against S.
epidermidis since even the highest concentration of THC used in the experiment did not eradicate
the biofilm.
26

Table 4. The pre-challenge biofilm densities for five species of Gram-positive bacteria and the
MBECs of CBD, THC, and CBG against each species.
Species
MDR MRSA
S. aureus
S. intermedius
S. hycius

Pre-challenge
biofilm density
(CFU/mL)
2.6 × 105
2.3 × 106
1.8 × 106
4.5 × 105

CBD MBEC
(μg/mL)

THC MBEC
(μg/mL)

3.91
7.81
31.25
3.91

31.25
62.5
15.63
7.81

CBG MBEC
(μg/mL)
3.91
15.63
15.63
7.81

35.0

Concentration (μg/mL)

30.0
25.0
20.0
MRSA
S. aureus

15.0

S. intermedius
S. hycius

10.0
5.0
0.0
CBD

THC

CBG

Type of Cannabinoid

Figure 16. The MBECs of CBD, THC, and CBG against 4 species of Gram-positive bacteria.

Figure 17 illustrates the overall trend in cannabinoid activity across the 4 species of bacteria
using viable cell count. THC seems to be least active and have the highest MBEC (M = 24.42
μg/mL, SD = 13.67 μg/mL) against the bacteria, then CBG (M = 7.82 μg/mL, SD = 5.53 μg/mL),
and lastly, CBD which closely followed CBG and was the most active and had the lowest MIC (M

27

= 7.33 μg/mL, SD = 6.05 μg/mL) against the bacteria. Again, there is a high degree of variation
across the species of bacteria as indicated by the high standard deviation shown by the error bars.
40.0

Concentration (μg/mL)

35.0
30.0
25.0
20.0

15.0
10.0

5.0
0.0
CBD

THC

CBG

Type of Cannabinoid

Figure 17. The average MBECs of CBD, THC, and CBG against Gram-positive bacteria (n=4).
Note: error bars represent one standard deviation from the mean.

The same multilevel linear regression model and two-way ANOVA was applied to the
viable cell count data that was applied to the absorbance data. Since a viable cell count of zero
indicates biofilm eradication, the data was logarithmically transformed after adding 1 to the viable
cell counts. The statistical outputs from this two-way ANOVA are reported in Table 5.
Table 5. Two-way ANOVA of the viable cell counts by species, cannabinoid concentration, and
the combination of these variables.
Measure
Species
Cannabinoid
Species + cannabinoid

F-value
7.309
58.740
2.084

P-value
3.32 × 10-5
< 2 × 10-16
0.0245

28

Based on these results and in contrast to the pattern seen with the turbidimetric measures,
there does appear to be a difference in the response to the cannabinoids across species overall.
Similar to the absorbance values, there was a significant difference in the variation between the
data for every specific combination of species and cannabinoid. For the cannabinoid concentration
measure, the P-value also indicates that the slopes of the antimicrobial dose response curve for
viable cell count are non-zero.

Comparing MICs to MBECs Across Cannabinoids and Level of Susceptibility
Based on the natural resistance to antibiotics in related to the structure of biofilms, a
comparison of the efficacy of each cannabinoid against planktonic versus biofilm bacteria was
done to see if the same pattern of resistance across staphylococcal biofilms is consistent for
cannabis extracts. Evident from Table 6, the MIC was not significantly lower than the MBEC
across the 4 species of bacteria for CBD, THC, and CBG (p = 0.328, p = 0.651, p = 0.215,
respectively).
Table 6. Paired two-sample t-test comparing the mean MBECs and MICs for each cannabinoid.
(n=4)
Cannabinoid type
CBD
THC
CBG

MIC
M
11.72
29.30
10.75

SD
13.15
24.19
5.86

MBEC
M
7.33
24.42
7.82

SD
6.05
13.67
5.53

df

t-value

p-value

4
4
4

1.166
0.501
1.57

0.328
0.651
0.215

To determine if there was any pattern of resistance to the cannabinoids in strains that were
MDR, the mean MICs and MBECs of the cannabinoids were compared between the clinically
isolated MDR MRSA and the non-resistant S. aureus. From Table 7, there was no significant
difference in the activity of the cannabinoids against drug-resistant and non-resistant strains of S.

29

aureus (MIC p = 0.195, MBEC p = 0.270), despite non-resistant S. aureus having a higher MBEC
and MIC for each cannabinoid.
Table 7. Paired two-sample t-test comparing the mean MICs and MBECS between MRSA and S.
aureus. (n=3)
Measure
MIC
MBEC

MRSA
M
SD
13.02
15.79
13.02
15.79

S. aureus
M
SD
28.65
29.58
18.23
11.93

df

t-value

P-value

3
3

-1.921
-1.511

0.195
0.270

DISCUSSION
Through developing the procedure and conditions for growing biofilms in the laboratory,
we showed that nine species of bacteria, both Gram-positive and Gram-negative, MDR or nonresistant, can be cultured to an appropriate biofilm density of 104 to 106 CFU/mL for the screening
of antimicrobial agents (Innovotech 2019). The biofilm densities of all the bacteria fell within this
range except for the MDR P. aeruginosa which had an average biofilm density of 1.7 × 107
CFU/mL from two growth trials. Had we seen any activity of the cannabis extracts against this
strain, the growth would have been adjusted accordingly to maintain biofilm growth within that
window. Based on the widespread ability for bacteria to form biofilms and the adaptive advantage
to grow in biofilms for pathogens, the ability to culture a diverse set of bacteria at the same
conditions was expected. Likewise, based on the characteristics of biofilms and the pathogenic
aptitude for establishing productive biofilm communities on all kinds of surfaces, the observed
increase in biofilm density compared to the initial planktonic population used to inoculate the
MBEC plate was anticipated as well (Muhammad et al. 2020).
Using the MBEC assay, CBD, THC, and CBG have all shown the ability to eradicate an
established Gram-positive biofilm and inhibit the growth of bacteria that had dispersed from the

30

biofilm. Even at a maximum concentration of 125 μg/mL there was no visible effect against the
Gram-negative, MDR E. coli or MDR P. aeruginosa. Similarly, none of the terpenes tested against
the MDR strain of MRSA had any visible activity. The outer membrane of Gram-negative bacteria
reduces the penetrance of cannabinoids, so the MIC of THC and CBD falls outside of the useful
therapeutic range at approximately 100 to 200 μg/mL (Van Klineren and Ten Ham 1976; Farha et
al. 2020). This is coherent with the apparent lack of activity of the cannabinoids against the Gramnegative species. Eugenol has broad-spectrum antibiofilm activity and can inhibit biofilm
formation, eradicate existing biofilms, and kill planktonic cells with an MIC ranging from 100
μg/mL to 400 μg/mL (Yadav et al. 2015). Again, visible inhibition may have been missed at the
starting concentration of 125 μg/mL so determining the MIC and MBEC for eugenol and other
terpenes may have been out of the range of our chosen concentrations.
Cannabinoids can inhibit formation of MRSA biofilms and eradicate biofilms that have
already been formed. Notably, cannabinoids target the cytoplasmic membrane of Gram-positive
bacteria with MICs of 2 μg/mL for CBD, CBG, and THC and a MBEC of 4 μg/mL for CBG (Farha
et al. 2020). In other studies, the MIC for THC and CBD against S. aureus has ranged between 2
to 5 μg/mL and 1 to 5 μg/mL, respectively (Van Klingeren and Ten Ham,1976); the MIC for CBD,
CBG, and THC against MRSA ranged from 0.5 to 1 μg/mL, 1 to 2 μg/mL, and 0.5 to 2 μg/mL,
respectively (Appendino et al. 2008); and the MBEC for CBD against MRSA ranged from 2 to 4
μg/mL (Blaskovich et al. 2021). Although many of the MBEC and MIC values reported here for
the 5 species of Gram-positive bacteria were higher than the ranges previously reported, some of
the MBEC and MIC were at 3.91 μg/mL which falls within a similar range of the studies above.
After fitting the dose response curves from both the viable cell counts and turbidimetry
data to a linear regression, we showed that the slopes of the regression are non-zero and negative

31

supporting that when the concentration of cannabinoid is increased, the growth of the bacteria is
inhibited until reaching the point where no growth occurs. This is consistent with the dose response
patterns of bacterial growth across different screening assays for cannabinoid activity (Blaskovich
et al. 2021; Farha et al. 2020; Martinenghi et al. 2020). There was variation in the responses to
each cannabinoid across species and across cannabinoids within the same species for the
absorbance data and the viable cell counts. The only exception to this was that there was a
consistent response to the cannabinoids across species as illustrated by the regressions analysis of
the absorbance data. Being that Gram-positive bacteria, especially within the same genus, have a
similar physiology, it would be expected that they should have a comparable response to the
cannabinoids (Farha et al. 2020). In this case, the absorbance data is consistent with a standard
response, whereas the viable cell count suggests otherwise. The variation across cannabinoid type
for the same species was also unexpected based on the MIC and MBEC values cited above
whereby the values are mostly consistent across CBD, THC, and CBG. In contrast, although the
MIC and MBEC values for CBD and CBG are generally comparable across species, the values for
THC are usually much higher.
The differences between the MICs and MBECs for CBD, THC, and CBG across the
bacteria were insignificant, however, the means MBEC for each cannabinoid was lower than the
mean MIC in every case. Again, this agrees with the concentrations reported in the studies above
which show that the same concentration is usually effective against both biofilms and planktonic
bacteria. This finding suggests that in contrast to many antibiotics, cannabinoids can equally target
both types of growth, both by inhibiting the maintenance and formation of biofilms and by directly
killing the bacteria. Because of the importance of membrane integrity in the release of vesicles for
quorum sensing and subsequent biofilm formation, these results support the hypothesized

32

mechanism that cannabinoids target the cytoplasmic membrane which would both inhibit biofilm
growth and directly eliminate cells. This would be in addition to the potential bactericidal impact
of cannabinoids at disrupting DNA and protein synthesis (Blaskovich et al. 2021).
A last point of interest is the question of if MDR strains already possess some resistance to
cannabinoids. Critically, our results show that although insignificant, the average MIC and MBEC
across cannabinoids was higher for the antibiotic-susceptible S. aureus strain compared to the
MDR MRSA. These results suggest that the genes for multidrug resistance in clinically isolated
specimens confer no resistance to cannabinoids which support the development of cannabinoids
as functional antibiotics. In line with this conclusion, the frequency of CBG resistance in MRSA
is estimated to be less than 10-10 and the natural tendency to develop resistance to drugs that target
the membrane is lower compared to drugs that target other cellular mechanisms (Farha et al. 2020;
Hurdle et al. 2011).
There are several limitations from this project that are important to acknowledge. To begin,
we opted to screen cannabis extracts against a more diverse sample of bacteria rather than
completing repeated trials with the same bacteria. Although this provided better evidence for the
applications of cannabinoids across pathogenic staphylococcal bacteria, it increases the risk of
effect errors and thus, reduces the reliability of the conclusions. Another limitation is that using
viable cell counts is an estimate of the true number of cells which introduces some uncertainty
when screening compounds for antimicrobial activity. Miscounting colonies can also result in error
since applying a dilution factor amplifies that mistake drastically. With that said, turbidimetry is
not subjective and in this case, provides construct validity to viable cell count by using it as a
simultaneous measure of antimicrobial activity. Although all the biofilm densities before exposure
to the cannabinoids fell within an appropriate range for antimicrobial susceptibility testing, slight

33

differences in the concentration of cells could influence the values for the MIC and MBEC of the
cannabinoids. Therefore, comparisons between different species should be made cautiously to
consider the possible implications of the starting biofilm population. Lastly, by viewing the
antimicrobial dose response curves, it is likely that the curves would better fit a logistical model
rather than a linear model for regression analysis. However, because there were sometimes
increases in growth at higher cannabinoid concentrations, a logistic model could not be applied.
Although this does not negate the conclusions drawn from the linear regression analysis and
corresponding two-way ANOVAs, a logistical model would provide conclusions that would be
more representative of the response curves.

CONCLUSIONS AND FUTURE WORK

Biofilms present a challenge to the development of antimicrobials, consequently putting
immense pressure on the healthcare system. Compounded by the growing antibiotic resistance
crisis, developing novel antibiotics is a necessary area of research and cannabis extracts represent
a potential antimicrobial reservoir. The longstanding stigma that has previously set up barriers
against the progression of cannabis research is beginning to wane and as such, investments in
understanding the value of cannabis extracts for human health should be emphasized across
research and government policy. The evidence from this study show that cannabinoids can
effectively disrupt the maintenance of Gram-positive biofilms and kill cells within the matrix
illustrating their potential as alternatives to antibiotics. An important consideration when screening
potential antimicrobial agents is whether they are bactericidal or bacteriostatic. Although there is
some overlap between the two terms, bactericidal agents correspond to those that kill bacteria,
whereas bacteriostatic agents correspond to those that stop the growth of bacteria (Pankey and
34

Sabath 2004). Here, we show that cannabinoids are bactericidal since they can completely
eradicate a biofilm as indicated by the viable cell count measures. Drug development is a
competition between pharmaceutical innovation and the mutating genome of widespread bacteria,
and this investigation has the potential to contribute to the treatment of untreatable bacterial
infections. We hope to continue evaluating the use of cannabis extracts for clinical applications
not only to create new antimicrobial agents, but to broaden the search scope to sources that have
once been disregarded.

Considering the wide variety of chemicals within a raw extract of cannabis, cannabinoids
and terpenes likely interact in many ways within the plant and represent an area of research that
could optimize the use of cannabis in medicine. Combination antibiotic therapy is already a
possible alternative to monotherapy that can prevent antibiotic resistance. Checkerboard assays
are a method of testing combination therapy and have been previously implemented to investigate
the synergism between different types of currently available antibiotics and the synergism between
cannabinoids and antibiotics. Alone, CBG has reduced activity against Gram-negative bacteria due
to the additional outer membrane, however, antibiotics that increase membrane permeability can
be used in concert with CBG. Using a checkerboard assay, combining nonlethal concentrations of
polymyxin B with CBG reduced the MIC of CBG from being nonexistent to 1 μg/mL (Farha et al.
2020). Similar synergism was observed between polymyxin B and four other cannabinoids as well.
Therefore, these interactions should be further examined by using checkerboard assays to evaluate
the synergistic effects of multiple cannabis extracts against multidrug-resistant bacteria.
Furthermore, since the exact mechanism of action of cannabinoids against bacteria remains
elusive, research should focus on beginning to resolve these complex processes. Only then can we
completely advance the therapeutic applications of cannabinoids against infection.

35

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APPENDIX A – ANTIBIOGRAMS

Figure 10. Antibiogram for E. coli #1.

Figure 11. Antibiogram for E. coli #2.

40

Figure 12. Antibiogram for E. coli #3.

Figure 13. Antibiogram for P. aeruginosa #1.

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Figure 14. Antibiogram for P. aeruginosa #2.

Figure 15. Antibiogram for P. aeruginosa #3.

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Figure 16. Antibiogram for methicillin-resistant S. aureus #1.

Figure 17. Antibiogram for methicillin-resistant S. aureus #2.

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Figure 18. Antibiogram for methicillin-resistant S. aureus #3.

Figure 19. Antibiogram for methicillin-resistant S. aureus #4.

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APPENDIX B – DOSE RESPONSE CURVES
S. epidermidis

B

MRSA

Hi

S. aureus

S. epidermidis
S. hycius
S. hycius

F

S. intermedius

S. intermedius

B

Log Viable Cell Count (CFU/mL)

S. aureus

B

Log Cannabinoid Concentration (μg/mL)

Figure 18. The antimicrobial agent dose response curves for five species of Gram-positive bacteria
based on viable cell count.

OD600 After 16 Hours of Growth

S. aureus

S. epidermidis

B

MRSA

Hi

S. aureus
S. epidermidis
S. hycius

F
S. hycius

S. intermedius

S. intermedius

B

Log Cannabinoid Concentration (μg/mL)

Figure 19. The antimicrobial agent dose response curves for five species of Gram-positive bacteria
based on turbidimetry.

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APPENDIX C – BIOFILM GROWTH CONDITION RESULTS

To begin, three types of complex media were used to determine which broth produced the
pegs with the best biofilm coverage. These included Tryptone Soya Broth, Luria-Bertani broth,
and Nutrient Broth. Each of the three MDR bacteria species were incubated in each of the three
media on a single MBEC plate. For the first attempt at growing the biofilms, the plate was
incubated at 37 °C and 110 rpm for 24 hours (Harrison 2012; Sandberg et al. 2008). After removing
the plate from the incubator, all of the wells around the perimeter of the plate and some of the
wells in the interior of the plate had no broth left due to evaporation at a high temperature and low
humidity. For the second attempt, the plated was parafilmed incubated at 37 °C and 110 rpm for
16 hours with two 1000-mL beakers filled with water. By including the water and decreasing the
incubation time, the humidity in the incubator reached approximately 65% and the evaporation of
broth in the wells was limited. In addition, we assumed that parafilming the plate would reduce
evaporation and so the plate was parafilmed before every incubation in the protocol.

Following incubation, biofilm growth with each type of media was qualitatively observed
by removing the pegs with flame-sterilized pliers, rinsing the pegs in phosphate buffered saline
(PBS) to remove cells that had dispersed from the biofilm, and staining the biofilm with crystal
violet. The pegs were placed in an empty petri plate and examined under a stereomicroscope as
shown in Figure 20. Based on the appearance of the stained biofilms of each bacteria species
incubated in each medium, we determined that Tryptone Soya Broth (TSB) produced the biofilms
that best covered the pegs, and this media was used in all subsequent experimental trials to grow
the biofilms.

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Figure 20. Examples of biofilms grown in TSB and stained with crystal violet (Top left: sterile;
Bottom left: MDR E. coli; Top right: MDR P. aeruginosa; Bottom right: MDR MRSA).

47