investigation of the microbial ecology within a

Investigation of the Microbial Ecology Within a Residential Hall Bathroom

Elshaday Zelalem Sendek

Department of Molecular, Cellular, and Developmental Biology

University of Colorado, Boulder

Defense Date: April 8th, 2019

Thesis Advisor

Dr. Ken Krauter, Department of Molecular, Cellular, and Developmental Biology

Honor Council Advisor:

Dr. Robin Dowell, Department of Molecular, Cellular, and Developmental Biology

Defense Committee:

Dr. Matt McQueen, Department of Integrative Physiology

Dr. Robin Dowell, Department of Molecular Cellular and Developmental Biology

Dr. Ken Krauter, Department of Molecular Cellular and Developmental Biology

Investigation of the Microbial Ecology Elshaday Z. Sendek Within A Residential Hall Bathroom

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ABSTRACT

The human microbiome is becoming just as important to understand and classify as the

human genome itself, due to its impact on human health. Because of our symbiotic relationship with

microbiota, the fact that we tend to acquire bacteria from our built environments, and also acquire

them from one another, it is essential to understand them in and around our lived environments.

Residential halls at universities are prime candidates to study, to understand that relationship. In this

study, we investigated the microbial ecology within a Residential hall bathroom. We categorically

looked at gender differences, location within the bathroom (i.e., sinks, toilets, and showers) and

variation in sanitation. Collected samples were to be analyzed by V4 PCR amplicon DNA

sequencing. In this thesis, I report the successful collection and quality control of the set of samples

and their preparation for sequencing using a relatively novel DNA preparation method. Future

research will characterize and analyze the identities and abundances of bacteria in this important set

of dormitory locations.


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INTRODUCTION

Understanding The Human Microbiome

The microbiome and complexities of that environment have been studied since 1680 when

Antonie Vas Leewenhoek studied his own oral and fecal microbiota (Ursell et al., 2012). To describe

studies of microbial populations living in humans it is useful to define terminology. The human

“microbiome” is the collection of all microorganisms (i.e. the microbiota) living on or within a

human niche; thus, the human gut microbiome is the collection living in the gut. Metagenomics is

the study of the composition of all of the genes in a microbial population (Ursell et al., 2012). 16S

rRNA amplicon sequencing is a subset of metagenomics that is limited to the sequences of the

unique regions of the microbial 16S RNA-encoding genes and is used for rapid and inexpensive

identification of a microbiome composition (see below) (Grice and Segre, 2012).

The realization that 16S amplicon sequences may be used to identify microorganisms grew

out of early work of Woese and colleagues who developed the methods used to create phylogenetic

trees based on these sequences (Woese, 1987). The premise of their work led to the use of specific

hypervariable regions of the 16S genes along with PCR to assign taxonomy (Grice and Segre, 2012).

The recognition of the potential to study entire microbial populations rapidly using methods that did

not require the culturing of individual bacteria led to an innovation conducted by the National

Institutes of Health in 2007 called The Human Microbiome Project (www.bcm.edu). Its ongoing

goal is to identify, characterize, and analyze the human microbiome as it relates to health and

diseases (www.bcm.edu).


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Human Microbiome Diversity and Functionality

Both genes and environment influence the establishment of the microbiome in humans.

During gestation in utero, fetuses are in a relatively sterile environment. However, after the placenta

ruptures, they exit through the vaginal canal where almost immediately, different parts of their

bodies become colonized with microorganisms including bacteria, fungi, and archea creating the

human microbiome (Morgan and Huttenhower, 2012, www.bcm.edu). Each person has 10-100

trillion symbiotic microbial cells living within specific areas of the human body (Ursell et al., 2012),

including “external and internal surfaces, such as the gastrointestinal tracts, skin, saliva, oral mucosa,

and conjunctiva with the colon and skin having the highest numbers of bacteria respectively (Sender,

Fuchs, Milo, 2016). Although there is uniqueness to each individual’s microbiome (Human

Microbiome Project Consortium, 2012) there are dominant signature taxa in each niche (Grice and

Segre, 2012). Figure 1 shows the dominant taxa and how they differ within an individual.

The human genome is comprised of ~22,000 genes that may produce approximately 150,000

gene products due to splicing (Ursell et al., 2012). The MetaHIT Consortium reports that there are

~3.3 million non-redundant genes specifically in the human gut microbiome (Ursell et al., 2012).

When compared to the overall population, humans are 99% identical to one another via the human

genome, but are 80-90% different in the microbiome of their hand and gut (Ursell et al., 2012). This

illustrates the gravity of diversity of the microbiota that we have within ourselves and with one

another.


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Figure 1. Diversity of the Microbiome From: The Human Microbiome: Our Second Genome The diversity of the different bacteria in a variety of niches is shown. Phyla (Actinobacteria (gram-positive), Bacteroidates (gram-negative) Firmicutes (gram-positive), Fusobacteria (gram-negative), and Proteobacteria (gram-negative)) and genera are color coded (Grice and Segre, 2012). The figure is derived from data collected from the first five-year National Institute of Health funded Human Microbiome Project of 242 subject study (Grice and Segre, 2012).

Bacteria are well known to be pathogenic. For example, Streptococcus suis which causes

meningitis, leading to a 3% mortality and only 36% of patients attaining full recovery (Samkar et al.,

2015) supports the perception that all bacteria are harmful. Recent research has begun to prove that,

in fact, bacteria are a crucial part of life. The roles that bacteria play in our bodies vary from helping

in the regulation of our immune system and producing vitamins, to combating pathogenic bacteria,

maintaining gut homeostasis (www.bcm.edu, Hänninen et al., 2015) and so much more. For


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example, having diverse gut microbes specifically protects the gut from pathogenic bacteria

colonization leading to gastrointestinal diseases (Hänninen et al., 2015). Figure 2 demonstrates

some of the functions that bacteria have in relation to aiding human health. Since the environment

can affect the establishment and maintenance of our microbiomes, it is important to get information

about what bacteria we are exposed to in our “built environment”. This is the motivation for my

project.

Figure 2. Functions of Gut Microbiota Image constructed in Microbiome Therapies Suffers Setback with Phase II Failure outlines the important functions that the gut microbes offer to human health (Gameiro, 2016).

Microbiota Development, Relationship to Diseases, and Association to Environment

As Figure 3 shows, colonization by microbiota occurs through an infant’s pre- and post-natal

development. Children’s microbiomes are less stable than the mature adult microbiome that persists


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through one’s lifetime (Browne et al., 2017). As the child continues on to adulthood, “urbanization

(environment), lifestyle, diet, age, and genetics all begin to play a role in the microbiota that

individuals possess (Sharma and Gilbert, 2018). It has been proposed that especially in industrialized

societies that represent ~54% of the world population, observed increases in chronic diseases such as

inflammatory bowel disease (IBD), cancer, allergies, type 2 diabetes, depression and vascular

disorder may be due to lack of exposure to diverse bacteria (Ehrlich, 2016; Yu, 2018). Although

debatable, many believe that microbial exposures are vital to human development (Sharma and

Gilbert, 2018).

Figure 3. Microbiota from Gestation to Childhood This image depicts microbial composition from prenatal to postnatal. It illustrates that upon gestation, although debatable, there is a sterilized environment. Then as the child develops and enters the world due to different biological, environmental, and dietary ext. exposers and life styles the gut microbiome grows in complexity and magnitude (Milani et al., 2017).


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The focus of my thesis is that the microbiomes of college students may be influenced by the

environmental exposures in the dormitory. I have tried to study if there is a relationship between

environmental microbiota in the common areas of the dormitory and the microbes that are seen in

individuals living in the dorms. Although exposure to environmental microbiota is important in

decreasing the risk of disease stated above, it is important to consider both pathogenic and non-

pathogenic exposures since all may influence health. Among the most important pathogenic bacteria

that affects humans are Staphylococci and Streptococci (Török and Day, 2005). As mentioned above,

Streptococcus suis which is common in the environment can cause meningitis, leading to a 3%

mortality rate and significant long-term health effects on survivors (Samkar et al., 2015).

Staphylococcus aureus causes up to 90,000 annual deaths and approximately $6 billion in health

care costs (Tonn and Ryan, 2013). A study done at 15 university bathrooms illustrated that

Staphylococcus aureus was positive in all bathrooms tested, with the highest occurrence seen on

shower floors (Tonn and Ryan, 2013). I expect to observe similar results but will also be interested

in other exposures both pathogenic and non-pathogenic. The dichotomy between pathogenesis and

symbiosis illustrates the importance of working to understand and analyze the structural and

functional makeup of bacteria within humans and how exposures contribute to health.

University of Colorado Boulder Libby Residential Hall Microbes

The Libby Residential hall bathroom is a promising location to study human and microbial

interactions. CU’s Libby Residential hall has fairly controlled access to the bathrooms in that the 46

residents had nearly exclusive access and use of their respective floor bathrooms, although obviously

occasional visits from guests were possible. There is only one bathroom on the men’s floor and one

bathroom on the women’s floor. This “forces” students to have consistent contact mainly with one


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bathroom multiple times per day. In the two studies of a similar built environment, it was shown

that residential hall bathrooms had a diverse collection of microbes, even with usual measures of

sanitation in place (Tonn and Ryan, 2013, Decker and Slawson, 2012). One of the studies observed

that male residential hall restrooms had higher levels of microbes than female residential hall

restrooms although my data will be useful to confirm this (Decker and Slawson, 2012). The research

that has been done allows for my work to either replicate these findings in a different location or

perhaps identify novel site-specific differences.

Previous studies have revealed that on a genus level the prevalence of some intestinal

microbiota vary by gender (Haro et al., 2016). The specific location of sinks, toilet seats, and shower

heads/floors are ideal locations for collection because these are spaces in these bathrooms that may

have student’s inner bodily fluids contributing to them and may be directly exposed to their bodies

during use. There has also been previous research demonstrating that the abundance of specific

microbiota varies with respect to location in bathrooms (Tonn and Ryan, 2013). The timing of

sampling should be carefully considered in view of the cleaning schedules of the test areas (see

methods and results). In this thesis, the sampling of bathroom areas was spread over a span of a

month to allow for variations due to cleaning processes to be averaged out.

This research was inspired by a paper entitled, “Cohabiting family members share microbiota

with one another and with their dogs” (Jin et.al. 2013). It states that humans that have constant

contact with co-inhabitors in a community will have correlated levels of bacterial diversity (Jin et al.,

2013). This led to the question of how much of those similarities are due to environmental contact,

in which individuals have similar microbiota because they are in contact with the same consistent


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environment. The work I have begun will also address whether or not gender differences reported

previously hold up well in a well-characterized set of living conditions in Libby hall. It will be

carried out over a one-month period with relatively frequent sampling that should reduce random

uncontrollable variables and may allow a better understanding of the effects and duration of cleaning

protocols used in the CU system. Finally, sampling a variety of sites may establish those areas with

the greatest influence on human microbiota.

MATERIALS AND METHODS

Sample Collection

Samples were collected from the University of Colorado Boulder Libby Residential hall.

Samples were collected using BBL Culture Swabs. The two tips provided by each BBL Culture

Swab were used on the surface of each location (Table 1), in three circular motions. Two bathrooms

were identified for sampling. One was a female bathroom located on the 1st floor southeast side that

was specifically accessible for 25 residents on that floor. The second bathroom was a male bathroom

on the 1st floor northeast side that was accessible for 25 residents on that floor. The samples were

collected twice a week from April 8 - May 3, 2018 (4 weeks). Samples were collected on Mondays

and Thursdays. Each of these days a total of 26 swabs were collected for a total of 208 swabbed

samples. Each swab contained two tips so the total potential sampling size was 416. Table 1

illustrates the specific sampling population. The 208 samples that were collected were at -80oC

freezer prior to processing.


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DNA Isolation

Ethanol-NaOH Protocol (EtNA):

DNA was extracted as described in Figure 4 (Vingataramin and Frost, 2015). One of the two

cotton swab tips was mixed with 500µl of solution E1 (Figure 4), and was added into each well of 96

well plates. Samples were then placed in a 75oC heating bath for 15 minutes then rapidly cooled on

ice for 5 minutes. Then after centrifugation of the samples at 4000rpm for 5 minutes in a swinging

bucket centrifuge fitted for 96-well plates for 5 minutes, the supernatant was placed into a 96-well

silica fiber filter plate pre-assembled onto a catch plate and centrifuged at 4000rpm for 5 minutes.

Flow through was discarded. The DNA, bound to the silica in the EtOH/salt lysate, was washed 2X

with 500µl of solution E2 (Figure 4) to remove contaminants. Final washing was conducted with

500µl of solution E3: Buffer. One drop of PolyvinylPolypyrrolidone (PVPP) (a cross-linked and

insoluble modification of Polyvinylpyrrolidone (PVP) (Kobeissi et al., 2018)), slurry was used to

inactivate polysaccharide Polymerase Chain Reaction (PCR) inhibitors known to be present in soil

Table1.Monday’sandThursday’sSampleCollectionPopulationMonday:12:00pm(Bathroomshaven’tbeencleanedfor3days)Female Male

• 5Sinks(Swab= sink drain)• 4Toilets(Swab=toilets seat)• 4Showers(Swab=showers drain, shower head)

• 5Sinks(Swab=sinks drain)• 4Toilets(Swab=toilets seat)• 4Showers(Swab=showers drain, shower head)

*Atotalof26swabswherecollectedtwiceaweek.Thursday12:00am(Bathroomswerecleanedthatmorning)Female Male



*Atotalof26swabswherecollectedtwiceaweek.


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samples (Rezadoost et al., 2016), and was placed into each of the .5ml 96-well collection plate; 50µl

of elution buffer was placed into each well and spun for 5 minutes at 4000rpm eluting DNA. An

additional elution of 50µl was combined with the first elution and stored at -20 oC.

Figure 4. Reagents for EtNA Protocol (Vingataramin and Frost, 2015). PVPP slurry was a modification made to adjust for DNA inhibitors.

DNA Quantification To Normalize Samples

The ability of DNA to produce PCR products and the efficiency of PCR on samples was

done using PCR. For the PCR reaction 5ul of H20, 5ul of HotStarTaq Plus Master Mix, 0.25ul of

16S rRNA Variable Region 4 (V4) 515f forward primer, 0.25ul of V4 806r reverse primer, and 2ul

PVPP Slurry

Mix approx. 10g PVPP (Sigma 110μ particle size + 10ml H2O

Solution E1 Makes 90ml

Final conc. What to add

200 mM NaOH 3.0ml 6N

2.25mM EDTA 0.4ml of 0.5M

61% Ethanol 57.0ml of 96% Et

H22O 29.6 ml

Solution E2 QIAGEN AW1; 50ml÷plate


2.5M GuHCL 11.9g

2.7 mM EDTA pH8.0 0.27ml 0.5M

10 mm Tris-HCl pH 8.0 0.5ml 1M EDTA

65% Ethanol 33.8ml of 96%

H22O 15.4 ml

Elution Buffer

DDW H2O

Solution E3 Makes 100ml


65% Ethanol 67.7ml of 96%

10 mm Tris-HCl pH 8.0 1.0ml 1M EDTA

H22O 31.3 ml


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of DNA were used. PCR reaction products were then run in a Gene Amp PCR System: first for 5

minutes at 95oC; then 45 seconds at 95oC, 1 minute for 50oC, and 1 minute 72oC for 35 cycles; and

lastly 10 minutes at 72 oC. PCR products were stained with DNA loading dye; then were subject to

2% agarose gel electrophoresis and bands were quantitated by densitometry. The densitometry was

analyzed using Image J, specifically the Fiji variant, to identify by integration of the area under peak

brightness (Ferreira and Rasband). The peaks observed are arbitrary numbers; they only have

meaning to the sample being discussed, and their essential use is to help in normalizing samples

(Miller, 2010). Each sample’s area was then placed on a meta-data sheet to do further analysis.

RESULTS

Experimental Report

In this report, I will cover the steps and results acquired from the collection, preparation and

quality control of the DNA sampling steps. It may be possible in the future to carry out the actual

DNA sequencing and analysis pending time and money.

I collected samples from the University of Colorado Boulder Libby Residential hall

bathrooms over the period of a month. Specifically, I extracted samples from male and female

restrooms twice a week, Mondays at 12:00 am and Thursdays at 12:00 am. The reason for this was

that the bathrooms only get cleaned through the weekdays at ~9:00 am. So on Monday mornings, the

bathrooms had not been cleaned for ~72 hours, whereas on Thursday mornings the bathrooms had

not been cleaned for ~24 hours. Collecting samples on these days and times allowed for additional

variable control and analysis.


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To collect samples I used BBL Culture Swabs and swabbed each surface studied and stored

them in an -80oC freezer. Each collection sample was two-tipped allowing for double the collection

of samples, so if tip 1 failed a second one was available for the same sample. Additionally, they were

frozen immediately upon collection at -80oC to protect samples from overgrowth. I collected

samples from sinks, toilets, and showers because they are locations in the bathrooms that have been

previously studied and have been known to exhibit accumulation of microbiota (Tonn and Ryan,

2013, Decker and Slawson, 2012). I isolated DNA using the EtNA protocol due to it being

inexpensive, effective and reliable (described further in discussions)(Vingataramin and Frost, 2015).

EtNA’s effectiveness is in the lysis and removal of membranes, carbohydrates, and proteins

(Vingataramin and Frost, 2015). I identified DNA in samples using PCR products of 16s rRNA

amplicon of the hypervariable V4 region as outlined in the Earth Microbiome Project

(http://www.earthmicrobiome.org). I evaluated the 16s rRNA because it is large, highly, conserved,

and found in all bacteria (Janda and Abbott, 2007) which makes it a perfect candidate when trying to

look exclusively at bacteria. The V4 region is specifically analyzed because it is located within the

16s rRNA, and due to its hypervariability it is different among different bacteria (Chakravorty et al.,

2007), so it highly effective in the classification of bacteria.

After PCR, the DNA products were subjected to 2% Gel Electrophoresis to quantify the

DNA using ethidium bromide staining and visualization with UV light. Pictures were taken and

analysis was conducted using software image J, Fiji variant, (Ferreira and Rasband). Using the areas

presented in Fiji of the samples (Table 2), I was able to normalize samples with the low peak

brightness areas being equal to 190, the medium peak brightness being greater than 190 but less than

1,500, and high peak brightness being 10,000. This allowed relative concentration of DNA in the


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samples to be estimated which could then be used to determine the volume of each sample to use for

DNA sequencing

Table2.SampleYields

SampleType,

LocationorDateof

Collection

NumberofSamplesWith

DNA/TotalSamples

Plates • Plate1 • Plate2

164/208->78.9%

SampleType,LocationorDateofCollection

NumberofSampleswithDNA/PerSpecificSampleType

Female 87/104->83.7%Male 77/104->70.0%1DayPostCleaning 78/104->75%3DaysPostCleaning65jb,mnjkjj86/104->82.7%Sink 69/80->86.3%Toilet 51/64->79.7%Shower 44/64->68.8%

The results I obtained are outlined in Table 2. DNA was identified in 164 samples out of 208.

Approximately 78.9% of samples had DNA. I observed that 13.6% more samples from female

bathrooms had DNA than male bathrooms. Also, there were ~7.7% more samples containing

detectable DNA on the third day after bathroom cleaning as compared to collecting it on the first day

after it was cleaned. Sinks had more samples that had bacterial DNA present then toilets (6.6%

more), and showers (17.5% more) which was almost triple the difference between sinks and toilets.

Overall, I observed that nearly 79% of samples taken yielded detectable levels of bacterial DNA. It


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is not entirely clear if this reflects reality (i.e. there is no DNA in the failed samples) or if this is due

to failure in DNA extraction or in PCR. Since there were two tips collected at each sampling, I was

able to reproduce the failure to find DNA in both tips. This lends confidence to the conclusion that

there were very low levels of bacteria present in those samples.

Experiments Still to be Done

DNA Sequencing Preparations

Multiplex sequencing will be carried out as previously described in “Genetic influences on

the human oral microbiome” (Demmitt et al., 2017). Briefly, PCR with multiplex V4 region primers

for the 16s RNA will be carried out on all samples in triplicate. After verifying by gel

electrophoresis, reactions of each sample would be pooled, purified and concentrated using Qiagen

spin column, and then samples would be pooled and submitted to the Biofrontiers DNA sequencing

facility. Illumina MiSeq on such samples has produced approximately 16,000,000 reads per run and

I would use 300-fold multiplexing to allow sequencing of all samples in a single run.

Sequence Analysis

Once sequencing reads are sent back, analysis will be done using LINUX-Based Quantitative

Insights into Microbial Ecology (QIIME2), the Bioinformatics software package

(https://qiime2.org). The point in using QIIME is to take sequencing data sent by Biofrontiers, and

generate phylogenetic and taxonomic characterizations of the samples. The steps that I will be

conducting are demultiplexing, picking and creating a table of Operational Taxonomic Units

(OTUs), assigning taxonomy and phylogeny, lastly identifying alpha and beta diversity among

samples (Kuczynski et al., 2011).


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DISCUSSION

I set out to investigate the microbial ecology within a residential hall bathroom; specifically,

as it relates to gender differences, locations within the bathroom and timing of cleaning. My goal

was to add to the growing research and confirm relationships of microbiota within this built

environment and analyze the complexities and abundance of pathogenic and non-pathogenic

bacteria. The process to reach my goal included: sample collection, DNA isolation via EtNA

protocol, DNA quantification to normalize samples, DNA sequencing, and sequence analysis of the

complexity and abundance of microbial populations over time and geography. Due to time

constraints, I was only able to complete the first three processes. Based on previous research my

hypotheses were, shower floors would have the highest occurrence of bacteria (Tonn and Ryan,

2013), male restrooms will have a higher occurrence of microbes (Decker and Slawson, 2012), and

lastly the longer the insanitation of bathrooms the higher the prevalence of bacteria.

The results of my experiments were that 164 of the 208 samples (~78.9%) had DNA in them.

Looking at gender differences female restrooms had more samples that had bacteria then males.

Bathrooms that had not been sanitized after three days also had more samples that had bacteria than

bathrooms that had only been sanitized after one day. Lastly looking at locations within bathrooms, I

found that the sink had more samples that had bacteria than the toilet or shower. These results

illustrate the number of samples that had bacteria out of the total amount of samples, but do not

necessarily show that there are more or fewer bacteria in general since I cannot rule out technical

issues causing failure to find bacterial DNA.


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I was able to conduct this experiment due to the fact that I am a residential advisor within

Libby hall; therefore, it allowed me to have access to it 24/7 which made collecting samples easier.

However, there were several challenges that I had faced in doing this experiment which took me

longer to do than I had anticipated. Upon the first round of DNA isolation, not enough DNA was

being used in the PCR protocol so a re-run was done of all the samples with an increased amount of

DNA. Then within the first round of purifications, I was not getting enough yield of samples that had

DNA, so another round of purification needed to be done with adjustments to data, which took

several weeks. Lastly, upon acquiring these new data, I combined and normalized samples from this

and previous experiments using the areas collected in Fiji, which also took a couple weeks.

Why I chose to use EtNA over more standard isolation protocols

Bacteria can be either gram positive or gram negative which relates to the structure of the

external cell wall and its polysaccharide structure (Schaalje, 2018). Each species has slightly

different structures so finding a method to isolate all DNA from all microbial species found in my

samples was important. The Earth Microbiome Project is the international standards organization for

this sort of information (www.earthmicrobiome.org) and they urge the use of the Qiagen Power Soil

Kit for this purpose. It uses a combination of mechanical (glass bead-beating) and chemical

(quinidine HCL) steps to harshly liberate DNA from all classes of bacteria (www.qiagen.com/us/). I

had used this method in other experiments done in my lab and found this method effective but

extremely costly (more than $10/sample) and very time consuming for each preparation. Instead

after some control experiments, I settled on using a method described by (Vingataramin and Frost,

2015). This method is inexpensive, rapid and effective. Bacteria are heated to 75oC in NaOH and

ethanol to solubilize all protein, carbohydrates, and lipids, cleave all RNA to oligonucleotides and


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leave behind only single-strand DNA that can be readily used with PCR (Vingataramin and Frost,

2015). This protocol is both “quick and low cost” (Vingataramin and Frost, 2015).

In a detailed set of control experiments carried out in part by me and in part by another

undergraduate student in the lab, Hannah Chatwin, we were able to demonstrate that both the

quantity and quality of DNA isolated by each method quite were suitable for carrying out

amplification sequencing and both produced roughly similar outcomes for both quantity and

abundance of specific microbes as determined by sequencing (data not shown). Given that all of my

samples would be handled identically using the far less expensive (less than $0.10/sample versus

~$10 per sample) and far faster (30 minutes versus 6-8 hours), I settled on using the EtNA method

for all of my work.

Conclusion and Future Explorations

My results showed that some locations, genders, and times produced (based on gender or

area within the bathroom and day of the collection after being cleaned) more DNA than others. This

could be due to the fact that this reflects reality or could be due to some of the technical issues I

discussed above. Sequencing would need to be done to really examine those differences at the level

of abundance and complexity to determine if there are systematic reasons for the failures to find

DNA 100% of the time. Although this project was not completed, the community continues to

examine the microbiome interactions with humans and in particular, the effects of environment on

health and pathogenesis. The results of this pilot study would have allowed for further questions of,

how do the bacteria that students bring from different states and homes colonize their environment;

does one type of bacteria colonize an environment from one person and then does that same bacteria


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colonize the gut of all residents who are exposed to those bacteria? These experiments would need

IRB approval, due to the need to look at student’s microbiome in relation to their environment,

which adds another layer of complexity to this experiment. Residential halls offer a space where

there are natural controls such as the number of people who access a particular bathroom on a floor.

In addition, the students that live on that floor are voluntarily living in close proximity to one

another, which gives bacteria easy access to a variety of hosts. Due to our symbiotic relationship

with bacteria, understanding their lifestyles is imperative to understanding ourselves.


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ACKNOWLEDMENTS

Dr. Ken Krauter

Dr. Robin Dowell

Dr. Matt McQueen

Hannah Chatwin

Dr. Katharine (Kate) Semsar

Dr. Karen Ramirez

Dr. Andrea Feldman

The Biological Sciences Initiative (BSI)

The Undergraduate Research Opportunity Program (UROP)

investigation of the microbial ecology within a

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