Overview of the Scientific Problem

Before the sessions, all participants received a handout describing the experimental module (S1 Text). In the first section, the instructor provided a brief overview of the global problem and challenges of antibiotic resistance and the imperative need to discover novel antimicrobial compounds. This opened a brief discussion on recent efforts towards exploring natural, biological, and indigenous resources as antimicrobial agents [6–9]. Importantly, this overview emphasized the key feature of our laboratory module, whereby an interdisciplinary approach could aid the discovery and identification of novel antimicrobial compounds, especially those from natural sources.

Introduction to Experimental Equipment and Techniques

In the second section, participants were introduced to the experimental equipment and techniques used in the module (S1 Text). We used the disc diffusion assay to test the antimicrobial activity of different compounds [11, 12], a technique used in clinical and research microbiology laboratories to study the bacterial and fungal strains’ susceptibility to antibiotics [13, 14]. In the assay, compounds to be tested for antimicrobial activity are deposited on filter discs that have been placed on a lawn of bacterial cells. The perimeter at which the concentration of the compound falls below the inhibitory threshold defines the edge of the “zone of inhibition” in which the lawn does not grow [15, 16]. The size of this zone is set by the efficacy of the antimicrobial compound against the bacterial strain on the lawn and the active ingredient’s diffusion.

We created short video clips (S1–S9 Videos) to help familiarize participants with the experimental tools and techniques. Before the hands-on experiment section, participants were introduced to the principles of sterilization, techniques for sterilization of media and equipment, methods of differentiating sterile from nonsterile media, proper use of personal protective wear, precautions to take while working with a flame, levels of biosafety risk groups and biological containment, standard operating procedures for disposal of biological waste, and appropriate handling of biological waste spills. We reinforced these concepts at the end of the module and emphasized the importance of close coordination with biological safety personnel.

Hands-on Experiments

The hands-on sessions were conducted in improvised classrooms, so we used a risk group 1 (biosafety level 1) organism [17, 18]. The bacterial strain, growth media, and antimicrobial compounds used are listed in Table 1 along with the associated references [19–27]. Briefly, we used Escherichia coli DH5 a, a commercial broth, and eucalyptus oil, ethanol, and hydrogen peroxide as antimicrobial compounds.

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Table 1. Bacterial strain, media conditions, and antimicrobial compounds.

https://doi.org/10.1371/journal.pbio.1002044.t001

At the start of the hands-on section, the assistant instructor demonstrated the experimental steps of the disc diffusion assay, and then each participant performed the assay. The experimental scheme for the hands-on laboratory section is described in Fig. 1. Three days before the sessions started, E. coli DH5a was streaked onto Luria-Bertani (LB) agar and allowed to grow at room temperature for 24–48 hours. A day prior to each session, overnight bacterial cultures were grown in 10 mL LB broth in plastic Falcon tubes (50 mL). Cultures were incubated under static conditions at room temperature for 16–18 hours. (The facilities available included neither a shaker nor incubator.) We inoculated overnight cultures for the first session, and participants inoculated cultures for all the other sessions. Since bacterial lawn growth and zones of inhibition would be visible only after overnight incubation, participants used experimental plates from the previous days’ session to interpret the results of the assay.

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Figure 1. General scheme for the hands-on laboratory experiments.

Preparatory and experimental steps of the disc diffusion assay to test antimicrobial efficacy.

https://doi.org/10.1371/journal.pbio.1002044.g001

Participants noted the presence or absence of zones of inhibition caused by the test antimicrobial compounds and control and measured the width of the inhibition zone (X) as the distance from the edge of the disc to the edge of the zone (Fig. 2). Temperature of incubation, density of the bacterial lawn, bacterial strain used, and concentrations of the antimicrobial compound all influence the width of the inhibition zone. Differences in inhibition zone size allowed for comparison between the efficacies of different antimicrobial compounds and susceptibility profile of the bacterial strain. (Any open-access image analysis software (such as ImageJ) could be used to measure the inhibition zones [28].) Participants correctly determined that hydrogen peroxide was the most efficacious against the bacterial strain used, followed by ethanol and then eucalyptus oil.

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Figure 2. Representative zones of inhibition with different antimicrobial compounds.

Using the disc diffusion assay, representative zones of inhibition observed with (A) eucalyptus oil (X = 2 mm), (B) 70% ethanol (X = 5 mm), and (C) 3% hydrogen peroxide (X = 14 mm) on lawns of E. coli. Note that these are plates prepared by participants with no previous experimental biology experience. In (D), the zone of inhibition observed with the antibiotic tobramycin (10 μL of 50 mg/mL) is shown (X = 18 mm). Tobramycin was used as the molecular weight standard to calibrate the molecular weight of the test compound. Owing to budgetary constraints, participants could not be provided with antibiotics for testing purposes. This image is from the assay performed by the instructors to measure slope and critical time. For the analytical model, the width of inhibition (X) was measured as the distance from the edge of the disc to the edge of the zone. Scale bars are 5 mm.

https://doi.org/10.1371/journal.pbio.1002044.g002

At the end of each experimental session, we discussed biological safety and biohazardous waste disposal, including how these practices could be implemented at the participants’ home institutions. Following each session, bacterial cultures and agar plates were collected in designated bags for biological waste (with the biohazard symbol), treated with 10% household bleach (5.25% sodium hypochlorite) for 30–60 minutes [29], and then disposed of in the sink or trash.

Application of Experimental Data to an Analytical Model

An analytical model was employed to determine the physical characteristics of the active antimicrobial component as a way to prospect for novel antimicrobial agents, in which insights into the active ingredient would aid the development of a therapeutic formulation. This model is based on the disc diffusion assay [15, 16] and assumes that the active ingredient has a constant diffusion coefficient D and that a threshold concentration of the active ingredient is required to inhibit bacterial cells. The number of cells in the lawn increases as the lawn incubates, which decreases the per-cell concentration of the active ingredient, which therefore no longer causes inhibition after a critical time T_c of incubation. The model describes the width of the inhibition zone (X) as (1), in which C₀ is the concentration of the antimicrobial compound deposited on the filter disc. F is a function independent of C₀. C_c is the lowest concentration of the active ingredient required to cause measurable inhibition. The slope of X² as a function of ln(C₀) gives D, if T_c is known. We relate D to the molecular weight (MW) of the active ingredient using the Stokes-Einstein equation [30], thus: (2), in which A is the active ingredient and I is a known molecule that empirically calibrates the relationship between diffusion and molecular weight.

To measure the slope of X² as a function of ln(C₀), decreasing concentrations of the antimicrobial compound are deposited on bacterial lawns. After overnight incubation, the width of inhibition (X) for each concentration is measured. Using linear regression, the slope of X² as a function of ln(C₀) is obtained (Fig. 3A). To measure preincubation time, a given concentration of the antimicrobial compound is deposited on the bacterial lawn after different time intervals of incubation. After overnight incubation, the width of inhibition (X) for each time point is measured. Using linear regression, the time after which no inhibition is observed (X = 0 mm) is determined as the critical time of preincubation (Fig. 3B). Since these experiments are essentially variations in the disc diffusion assay, the hands-on session in the module would provide participants the requisite skills to perform these assays. Because time was limited to 3 hours total in one morning, participants used data we had taken in our research lab. Experiments were demonstrated using video clips (S8, S9 Videos), and the participants were guided through each step in the assay. Data for hydrogen peroxide (test antimicrobial compound) and the known antibiotic tobramycin (MW = 467.5 Da) were provided to the participants (S1 Text and S1–S4 Tables). Using a linear regression tool with which they were already familiar (such as Microsoft Excel), participants determined the diffusion coefficient and molecular weight of the test antimicrobial compound. The handout (S1 Text and S1–S4 Figs.) also contained the solutions to the exercise.

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Figure 3. Measuring slope of X² as a function of ln(C₀) and critical time (T_c) of preincubation for hydrogen peroxide.

(A) To measure the slope of X² as a function of ln(C₀), decreasing concentrations of hydrogen peroxide are deposited and the width of inhibition (X) for each concentration is measured. Using linear regression, the slope of X² as a function of ln(C₀) is obtained. (B) To measure preincubation time, a given concentration of hydrogen peroxide (30%) is deposited on the bacterial lawn after different time intervals of incubation. After overnight incubation, the width of inhibition (X) for each time point is measured. Using linear regression, the time after which no inhibition is observed (X = 0 mm) is determined as the critical time (T_c) of preincubation.

https://doi.org/10.1371/journal.pbio.1002044.g003

Participant Feedback

We did not conduct formal evaluations, but based on verbal feedback (Box 2), the participants found the module to be educational, scientifically challenging, engaging, and interesting. As physical scientists, they had almost no prior familiarity with biological experiments, and none had ever performed the disc diffusion assay. They found the choice of the scientific problem—antibiotic resistance—a relevant, relatable issue and appreciated the ease of performing the disc diffusion assay, which helped sustain their interest and boost their confidence. As theoretical and quantitative scientists, almost all of them were familiar with the laws of diffusion and diffusion-based analytical models. However, several participants reported that they had never thought of applying these conventional physical concepts to a biological problem. Some participants also said that the module provoked them into thinking of biology as a quantitative discipline in contrast to standard school and undergraduate curricula, which often teach biology as a purely descriptive science.

In one session, participants with no basic biology background had notable difficulty in understanding the science. This resulted in a substantial gap between their baseline knowledge and rudimentary concepts needed to understand this module. For example, one of the participants had never encountered the biological concept of a cell. While we did try to briefly address this lacuna in knowledge once we realized it, all the logical leaps that followed could not be explained in the limited time available. In subsequent implementations of this module, this could be overcome with a short, concise overview of basic biological concepts such as structure of a bacterial cell, bacterial growth and physiology, and cell death.

This was the first time this module was implemented as a science outreach tool. As a result, the logistics of executing the module in a resource-limited setting posed formidable challenges, such as shipping delays, a classroom and building not intended for biological work, and tailoring the program to suit the available budget. Owing to this, we did not focus on conducting a systematic assessment of the impact of this module on the participants. In the future, we plan to incorporate an evaluation step into this module by implementing the use of pre- and postsession surveys (using brief questionnaires) to gain a quantitative estimate of the outcome of this module on participants’ knowledge and attitudes about biophysical research. The questionnaire could be designed to not only measure participants’ understanding of the specific material presented (e.g., the problem of antibiotic resistance, potential modifications of the disc diffusion assay, and incorporating additional parameters into the analytical model) but also to gauge changes in their perceptions of larger concepts such as application of quantitative techniques to biological data and use of interdisciplinary approaches to address scientific challenges.