To our families

RICHARD J. MEYER

STACIE A. BROWN

Contents

Preface

About the Authors

Introduction

The scientific method

Experimental design

Big data

Documentation

Safety

challenge One

Identifying the bacteria causing infections in hospital patients

QUESTIONS BEFORE YOU BEGIN THE CHALLENGE

Lab One

BACKGROUND

Diversity and pure cultures

Bright-field and phase-contrast microscopy

Learning outcomes

I: Isolate bacteria from a mixed culture:

PROCEDURE: Streaking for isolated colonies

II: Examine bacterial cells under the microscope

PROCEDURE: Making a wet mount

PROCEDURE: Using the microscope

Preparation for next lab

QUESTIONS

Lab Two

BACKGROUND

Colony morphology and optimum temperature for growth

Cell shape and bacterial spores

The cell envelope

Learning outcomes

I: Describe the colony morphology of the unknown

II: Describe the characteristics of an individual cell viewed under the microscope.

III: Determine the optimum temperature for growth

IV: Determine if the unidentified microorganism is Gram positive or Gram negative.

PROCEDURE: Doing a Gram stain

Preparation for next lab

QUESTIONS

Lab Three

BACKGROUND

Modes of energy generation in bacteria

Learning outcomes

I: Can the unidentified microorganism grow in the presence of bile salts and ferment lactose?

PROCEDURE: Streaking cells on MacConkey-lactose plates

II: Can the unidentified microorganism ferment glucose?

PROCEDURE: Glucose fermentation test

III: Does the unidentified microorganism use cytochrome c during respiration (Gram-negative bacteria)?

PROCEDURE: Oxidase test

IV: Does the microorganism make catalase (Gram-positive bacteria)?

PROCEDURE: Catalase test

V: Is the microorganism motile?

PROCEDURE: Soft agar motility assay

QUESTIONS

Solving Challenge One

Preparing for Challenge Two

Challenge One Questions

BIBLIOGRAPHY

challenge Two

Confirming the identification of a microorganism by sequencing the 16S rRNA gene

QUESTIONS BEFORE YOU BEGIN THE CHALLENGE

Lab One

BACKGROUND

Classification of bacteria and 16S rRNA gene

Polymerase chain reaction (PCR)

Learning outcomes

I: Obtain enough DNA for sequencing: amplify the 16S rRNA gene by PCR

PROCEDURE: Setting up a PCR reaction

PROCEDURE: Diluting from stock solutions: using the formula C1 × V1 = C2 × V2

QUESTIONS

Lab Two

BACKGROUND

Agarose gel electrophoresis

Dideoxy DNA sequencing

Learning outcomes

I: Visualize the PCR product by agarose gel electrophoresis

PROCEDURE: Making an agarose gel and carrying out gel electrophoresis

II: Submit sample for DNA sequencing

QUESTIONS

Solving Challenge Two

BACKGROUND

Learning outcomes

Identifying the unknown microorganism from the 16S rRNA gene sequence

PROCEDURE: Preparing the sequence for analysis

PROCEDURE: Doing a BLAST search

QUESTIONS

BIBLIOGRAPHY

challenge Three

Choosing an antibiotic to alleviate the symptoms of Crohn’s disease

QUESTIONS BEFORE YOU BEGIN THE CHALLENGE

Lab One

BACKGROUND

Exponential growth

The bacterial growth curve

Pure cultures in liquid medium and the real world of bacteria

Learning outcomes

I: Construct a growth curve and calculate the generation time

PROCEDURE: Recording the optical density of a growing culture

II: Determine viable cell counts during exponential growth

PROCEDURE: Serial dilution of samples

PROCEDURE: Spreading cells on agar medium

QUESTIONS

Lab Two

BACKGROUND

Assaying for antibiotic sensitivity

Learning outcomes

Determine the MICs of different antibiotics for the Pseudomonas isolate

PROCEDURE: Setting up a MIC dilution assay

QUESTIONS

Solving Challenge Three

BIBLIOGRAPHY

challenge Four

Tracking down the source of an E. coli strain causing a local outbreak of disease

QUESTIONS BEFORE YOU BEGIN THE CHALLENGE

Lab One

BACKGROUND

Genomic diversity and horizontal gene transfer (HGT)

The shifting genome of many bacteria

Conjugation and other mechanisms of horizontal gene transfer (HGT)

Learning outcomes

I: Determine if chloramphenicol resistance can be transferred by conjugation

PROCEDURE: Doing a conjugation experiment on TSA medium

II: Determine if the donor strain for conjugation contains a plasmid

PROCEDURE: Rapid isolation of plasmid DNA

QUESTIONS

Lab Two

BACKGROUND

Strain typing

Learning outcomes

I: Determine if the plasmid DNAs from the lettuce isolate and the pathogenic strain are related

PROCEDURE: Doing a restriction digest

PROCEDURE: Agarose gel electrophoresis of the DNA fragments

Solving Challenge Four

BIBLIOGRAPHY

challenge Five

Using bacteriophage to identify the farm releasing pathogenic bacteria into a village stream

QUESTIONS BEFORE YOU BEGIN THE CHALLENGE

Lab One

BACKGROUND

History and properties of bacteriophage

Testing water purity

Learning outcomes

I: Determine the load of bacteriophage at each collection site

PROCEDURE: Filter the water samples to remove all the bacteria

PROCEDURE: Titer the phages in the sterile filtrates

Solving Challenge Five

QUESTIONS

BIBLIOGRAPHY

challenge Six

Evaluating the pathogenic potential of bacteria causing urinary infections

QUESTIONS BEFORE YOU BEGIN THE CHALLENGE

Lab One

BACKGROUND

Quorum sensing

Biofilms

Learning Outcomes

I: Determine if the hospital isolates form biofilms

PROCEDURE: Staining biofilms with crystal violet

II: Quantitatively analyze biofilm formation

PROCEDURE: Quantifying the amount of biofilm by spectrophotometry

III: Determine whether the hospital strains produce quorum sensing compounds

PROCEDURE: Using a reporter strain to detect quorum sensing

QUESTIONS

Lab Two

BACKGROUND

Swimming

Learning outcomes

I: Complete the analysis of quorum sensing

II: Assay the hospital strains for chemotaxis to different compounds

PROCEDURE: Testing for chemotaxis with the “plug-in-soft agar” assay

III: Determine the effectiveness of chemical cleaners

PROCEDURE: Testing for chemical effectiveness with the Kirby-Bauer disk diffusion assay

QUESTIONS

Solving Challenge Six

BIBLIOGRAPHY

Preface

Why write this lab manual? This project has been fueled by two observations. The first is that the content of many microbiology lab courses has increasingly lagged behind the principles and methods emphasized in lectures and textbooks. Second, some of these lab courses cling to the traditional method of exposing students to techniques as a progression of disconnected exercises. As a result, students learn many ways to characterize microorganisms, but not how to use these tools in an integrated way to solve problems in microbiology. These limitations can be found in the popular, commercial lab manuals and in many “in-house” manuals as well.

It is not hard to understand why laboratory courses in microbiology evolve slowly. First, there is often a lack of resources. Even small changes can result in the need for new equipment, large and small, and the cost can easily exceed the budget of many departments. These budgets are often prepared under the assumption that they will be stable from year to year, with little thought to the fact that a step up to more current content might require a one-time step-up in budget. Second, instructors often lack the time needed to test and then integrate new material into a lab course. In fact, there may be a disincentive for doing so: instructors are frequently evaluated by the “success” of their courses, meaning high enrollments and favorable student ratings, rather than by their content.

These problems can be less severe at well-endowed institutions offering teaching relief for course development and larger budgets. Many of these institutions produce their own lab manuals with up-to-date content. However, this content often reflects the interests and resources of the department and does not migrate well to other institutions, particularly small colleges.

We have tried to create a lab manual that offers a route to developing new content and pedagogy while remaining practical for the many undergraduate institutions that include a microbiology lab in the curriculum. We have sought to offer a course with the following characteristics.

1. The content conforms to the goals outlined in “ Recommended Curriculum Guidelines for Undergraduate Microbiology Education” (American Society for Microbiology, 2012).
2. Work is arranged around solving real-world problems (a “Challenge”), with an emphasis on cooperative effort by the class.
3. Techniques are introduced as they are needed, so that students can recognize their usefulness in working toward the solution for each Challenge.
4. Background sections are included to ensure that students have the information needed to understand what they are doing and how it is related to broader concepts in microbiology.
5. The course is largely modular. Instructors can extract one or more Challenges and integrate these into their own course.
6. The modules are amenable to various modes of in-depth assessment, including individual formal lab reports and group oral presentations.
7. The manual has an Introduction that provides the foundation for the proper practice of microbiology by including:

1. A description of the scientific method
2. An introduction to experimental design
3. Instructions for keeping a proper notebook
4. Safety guidelines for BSL1 (biosafety level 1) teaching laboratories outlined by the American Society for Microbiology (ASM)

8. All the organisms for the course are BSL1, in accordance with ASM guidelines. Conditions for handling BSL2 strains are not required.
9. Much of the necessary equipment can be found in microbiology teaching laboratories or borrowed from other lab courses.
10. Questions, ranked according to Bloom’s taxonomy, are provided for the lab sessions.
11. An accompanying Handbook for the Instructor covers in detail recipes, setup, and logistics.

Along the way it was also necessary to make some compromises:

1. The Challenges are based on situations found in the fields of medical microbiology and epidemiology. These areas engage students, many of whom are preparing for health-related careers, and they make up most of the content of many lab courses. Our emphasis is on problem-solving rather than on demonstrating the different areas of microbiology. The skills learned in the course, however, are broadly applicable to these other areas.
2. The steps to solving each challenge will differ somewhat from those used by professional medical microbiologists or epidemiologists. The differences reflect the need to include certain fundamental techniques and to organize the work so that it fits within lab periods.
3. The work is based on a particular set of strains. These strains were selected to demonstrate different microbial characteristics while keeping the collection within a reasonable size. Where substitutions are possible, this is indicated in the Handbook for the Instructor. Many colleges and universities have large collections of BSL1 and BSL2 strains for teaching purposes. In some cases, these collections extend back decades and their provenance is incompletely or inaccurately recorded. We think it is safer and more convenient to work with a small number of BSL1 strains.

We thank Elizabeth Emmert, Rachel Horak, Brooke Jude, Peter Justice, and Susan Merkel for their comments on an early draft of this book. Their criticisms helped point us in the right direction for producing something worthwhile. If we still managed to lose our way, the fault is ours. Thanks also to Annie Hollingshead and Tina Shay, who maintain the microbiology teaching labs at the University of Texas at Austin. Their knowledge and experience in making new experiments practical for large groups of undergraduates helped us keep our feet on the ground.

About the Authors

Richard J. Meyer, PhD, is professor emeritus in the Department of Molecular Biosciences at the University of Texas at Austin. He joined the Department of Microbiology at the University of Texas at Austin in 1978, and has been at that institution ever since. From the beginning of his career, Meyer has been interested in the hands-on aspect of teaching biology to undergraduates. He developed the introductory microbiology laboratory course currently used at the University of Texas at Austin. The pedagogical approaches in that course inspired him to develop the manual you hold in your hands. Over more than forty years, Meyer’s research was on the molecular mechanisms of replication and conjugative transfer of broad host-range plasmids.

Stacie A. Brown, PhD, is director of first year biology laboratories and a member of the Biology Department at Southwestern University. Prior to her current position, she taught microbiology courses for biology majors and pre-nursing students while also overseeing the microbiology labs at Texas State University. For several years, she also taught microbiology labs and courses at the University of Texas at Austin. Her experience teaching microbiology labs to thousands of undergraduates ensures that the challenge-based microbiology labs in this manual will work in any introductory laboratory course in undergraduate microbiology.

Introduction

This course is made up of six challenges. Each challenge contains a different problem, one that you might encounter as a microbiologist and be asked to solve. To do so, you will draw upon different techniques learned during the course, obtain and analyze the data you need, and then present the solution to the class or to your instructor.

The Scientific Method

Scientists make new observations about the world and then provide an explanation for these observations. This sounds simple, but it isn’t. For one thing, a new explanation must be viewed in the context of what has already been learned. Most often, the explanation is an extension or refinement of an earlier explanation. The new explanation is more powerful because it includes more observations, but is consistent with previous thinking. Occasionally, though, the new explanation is completely different from what was thought before. When that happens, it is an exciting moment in science.

How do we go from observation to explanation? The logical structure that scientists use, consciously or not, is called the scientific method, outlined informally in Fig. I-1. Scientists make careful observations and then identify those that need an explanation. They learn what is already known and then propose a hypothesis, a tentative explanation. The hypothesis must explain the new observation while being consistent with prior observations. In addition, it must be testable. This means that if the hypothesis is true, it will lead to predictions that can be tested by experiment. Scientists design and carry out these experiments and then ask whether the results match the predictions expected from the hypothesis. If they do not, the hypothesis is discarded and a new hypothesis accommodating these results is put forward.

Figure I-1  The steps in the scientific method.

The application of the scientific method as a series of steps is not always obvious from the course of scientific research and discovery. However, it still forms the logical underpinning of how scientists approach a problem. An example is the discovery that DNA is the carrier of genetic information (Fig. I-2). In 1928, Fred Griffiths, working with the bacterium Streptococcus pneumoniae, discovered that if you injected a mouse with dead cells of a virulent (disease-causing) strain, along with living cells of a strain that did not cause disease, the mouse developed an infection and died. By themselves, neither the dead virulent cells nor the living avirulent cells had this effect. Griffiths concluded that a “transforming principle” from the dead cells was converting the living cells to virulence. This was exciting because the acquired virulence was stably maintained as the cells grew and divided, indicating that the virulence trait was due to inherited genes. In other words, genetic information had passed from the dead cells to the living cells.

Figure I-2  Research leading to the discovery that the “transforming principle” is DNA.

What was the carrier of the genetic information? Since whole cells were used in the Griffiths experiment, there were many possibilities, but most of the bets were on proteins being the “transforming principle.” The reason was that only proteins were thought to be sufficiently complex and various in their properties to convey genetic information. A critical new observation was provided by Dawson and Sia, who showed that the transforming substance could be extracted as a soluble component from the virulent cells and then used to transform the avirulent strain in a test tube. This meant that it might be possible to purify the transforming principle and determine its chemical properties, a fact that was recognized by Oswald Avery and his laboratory group. The first attempts at characterization indicated that it was not a protein; rather, the properties were consistent with deoxyribose nucleic acid, or DNA, another and surprising new observation. Avery and his colleagues set about testing the hypothesis that DNA was the transforming principle. If the hypothesis was true, then it would lead to several predictions that could be tested by experiment. In every case, the experimental results were consistent with Avery’s hypothesis (Fig. I-2), resulting in a startling paper published by the Avery group in 1944. The idea that DNA was the carrier of genetic information was so unexpected that even Avery himself was reluctant to draw that conclusion, although, as you know, it has stood the test of time. A good review of this transformative moment in microbiology (no pun intended) is Cobb (2014).

There is an important but subtle logic behind scientific experiments. Science basically works by the process of elimination. Different hypotheses are tested by experiment and are discarded if the experimental results are inconsistent with the hypothesis. For example, the hypothesis that protein was transforming the cells was eliminated by the biochemical properties of the transforming principle. A hypothesis comes to be accepted when it is consistent with all the experimental results and when all other reasonable competing hypotheses have been ruled out by experimentation. “Reasonable competing hypotheses” depend on both our state of knowledge and our imagination. An awareness of this might have been one reason Avery was cautious about drawing the firm conclusion, in public at least, that DNA is the genetic material.

Experimental Design

From the foregoing it must be obvious that good experiments are the keystone of the scientific method. In designing an experiment, there are some things to keep in mind.

1. Does the experiment test the hypothesis? The purpose of a good experiment is to discriminate between hypotheses. Results that would be consistent with all the hypotheses under consideration do not help us to decide between them.

2. Is the experiment well controlled? Controlling all the possible variables except the condition you want to test is the best situation. In reality, this is not always possible, and there are often uncontrolled variables, variations in the experimental conditions in addition to what you want to test. Repeating the experiment multiple times, along with statistical methods, can sometimes be helpful when dealing with uncontrolled variables. However, statistical analysis cannot rescue experiments where the results are overwhelmingly influenced by the effects of uncontrolled experimental conditions.

3. Is the sample size large enough, and can the experiment be replicated? Sample size and replication of the experiment by yourself or others are closely related. Sometimes a result that seems to be real at first disappears upon replication. This is usually because the sample size was too small to begin with, and apparently real differences were just the result of chance. Suppose you hypothesize that a coin is weighted so that it will come up “heads” more often than “tails” after tossing. You decide to do the experiment of tossing the coin 8 times. If “heads” is the result 6 or more times, then you will conclude that your hypothesis is correct and you will publish your result. You get 7 heads and 1 tail during the toss, strong evidence, it seems, of a bad coin. However, while the probability of getting this particular result with a fair coin is only 3%, the probability of getting 6 heads or more is 14%. Your criterion for a bad coin would be met by a fair coin 14% of the time. The solution is to repeat the coin toss multiple times, which might seem obvious. However, many published experiments have not been sufficiently replicated. The inability to reproduce experimental results has become a major concern in the scientific community (Anonymous, 2016).

4. Are the accuracy and precision of your measurements adequate to support your conclusion? Accuracy refers to the closeness of a measurement to the true value, while precision refers to the reproducibility of a measurement: how often repeated measurements will give the same value. Both must be taken into consideration when drawing conclusions from an experiment. For example, a small but real change due to different experimental conditions might not be detected if the measurements are inaccurate. Imprecise measurements, on the other hand, could result in the real change becoming obscured by the random “scatter” of different data points.

5. Could observer bias influence the results? When scientists do experiments, they often have a desired result in mind, usually the one that supports their favorite hypothesis. This can lead to the unrecognized manipulation of results to favor this hypothesis. Sometimes rationalizations like “This value is much smaller than the rest: obviously there was a procedural error so it should be discarded” are used as a justification. This is a particular problem with students in lab classes. Often they think they know the expected outcome of an experiment. If some measurements do not support this result, they immediately assume that these were due to experimental errors and can be discarded.

For practice, consider the following situation:

A marine microbiologist suspects that iron in seawater stimulates the activity of a particular enzyme in the microbe she is studying. She takes eight samples of the seawater over the course of a month and adds the same amount of bacteria to each when she is ready to do the experiment. To four of these she also adds iron dissolved in seawater, and to the other four the same volume of seawater without iron. She then extracts the enzyme from the cells in each sample and assays the activity. The results are shown in Table I-1.

Table I-1  Effect of iron on enzyme activity

1. Does this experiment test the hypothesis?
2. The scientist is careful to use seawater as a control for the addition of iron. Does this mean that the experiment is well controlled? How could the experiment be better designed for stricter controls?
3. From the average result in each case, would you conclude that iron stimulates the activity of the enzyme? What is the underlying problem with these data? What changes would you make for a more convincing result?

Big Data

While the scientific method has been a fundamental rubric in research for many years, another way of making sense of the natural world has gained attention. This has come about as a consequence of “big data,” databases containing vast amounts of information. In biology, this includes most famously the databases of DNA sequences for different organisms. One of these, GenBank, contains more than 189,232,925 sequences, made up of 203,939,111,071 bases (as of June 2016) (Sarkar, 2016). Among these data are the complete sequences of all the DNA from each of more than 13,000 different types of bacteria (https://www.ncbi.nlm.nih.gov/genbank/). The database of DNA sequences of organisms is not the only large database: for example, catalogs of all the proteins encoded by an organism and their abundance in the cell are also being created (Sarkar, 2016), as are all the metabolic pathways.

How does one begin to make sense of the huge volume of biological data being generated? Some people have argued that an approach different from the scientific method is needed. Indeed, it has been claimed that the scientific method is obsolete and that it is no longer necessary to make predictions and then test these by experiment (Anderson, 2008). Instead, huge computers should be used to sift through the data and look for correlations. Hypotheses about causation are no longer necessary, because the database is so large that a correlation is bound to be significant.

While looking for correlations is useful, it has been sharply criticized as a platform for scientific discovery (Barrowman, 2014). As pointed out in this article, larger data sets will result in a larger number of meaningless or misleading correlations rather than fewer. It will still be necessary to sort out which correlations are significant. The credo “Correlation does not imply causation” applies, regardless of the size of the data set.

The scientific method is embedded in the solutions to the challenges in this course. Before you start each challenge, frame the challenge in terms of new information, hypothesis, and testing the hypothesis.

Documentation

How your results will be presented and evaluated will be up to your instructor. However, all scientific study includes a notebook.

A lab notebook is a scrupulously honest and complete record of what you did and the results obtained. Unlike other forms of scientific presentation, doing the work and observing the results is done at the same time as entries into the notebook.

Many students are tempted to record their activities haphazardly on pieces of paper, or trust their memory, and then transfer the information to a lab notebook later. This is particularly true if the instructor will view their notebooks during the course and the students are eager to provide polished results. However, this is not a notebook, because entries were made at a later time than the work. This practice is more likely to result in recording errors and increases the possibility that data will be altered to fit expectations, unconsciously or not. Notebooks do not have to be neat to contain scrupulously recorded, important information (Fig. I-3).

Figure I-3  Notebook of Albert Schatz, a graduate student in the laboratory of Selman Waksman at Rutgers in the 1940s. When carefully read, the notebook shows that it was Schatz who discovered the antibiotic streptomycin, not Waksman, who for many years received all the credit. From the Rutgers archives.

Important practices:

1. Use a permanently bound notebook. Loose-leaf notebooks often result in lost pages.
2. Write in ink.
3. Include the date with each entry.
4. If you make a correction, draw a line through the corrected entry (do not erase or make illegible) and then add the correction with the date.
5. For items that need to be added, such as photographs, apply them with tape or a paper glue. Do not keep them loose in the notebook. In addition, date the item and provide a legend or labels as appropriate. When it is time to present your data, you want to be completely clear what the inserted item is showing.
6. Include important calculations in the notebook. What is an important calculation? If you are dividing 500 ml of buffer into two equal amounts, you don’t have to show the calculation 500/2 = 250, but calculations critical for the success of the experiment should be recorded, for example, calculating the weight of a chemical that would be required to make 100 ml of a 0.01 M solution, or the volume of a 0.05 M stock solution needed to make 100 ml of a 0.01 M solution.

If you work in any area of science, your notebook might become very important. A dramatic example is the ongoing battle over who owns the rights to the CRISPR (clustered regularly interspaced short palindromic repeats) system for genetic engineering (Regalado, 2015). This technique, which allows the precise modification of DNA in eukaryotic cells, was developed by two different lab groups (at least). The institutions that house these groups are both claiming patent rights for a process that could earn millions or even billions of dollars in licensing fees. The patent office has decided that whoever developed the procedure first will be awarded the patent. Thus, it will all come down to the notebooks of the different scientists: who did what first?

Develop the habit of keeping a good notebook. Your instructor may ask to see your notebook or assign notebook checks for part of your grade.

Safety

The impact of different microbes on humans ranges from beneficial, as is the case with many of the bacteria found in our digestive tract, all the way to deadly. Bacteria known to cause disease are called pathogens. However, there is no clear line between pathogenic and nonpathogenic microorganisms. The Centers for Disease Control and Prevention (CDC) categorizes microorganisms and viruses into four biosafety levels: BSL-1, BSL-2, BSL-3, and BSL-4. The CDC and National Institutes of Health have established safety guidelines for each biosafety level.

BSL-1 organisms pose minimal risk to users. Nonpathogenic strains of Escherichia coliPseudomonas aeruginosaMycobacterium tuberculosis