May 2015

Exploring the Microbial Communities Within andAround Us
Next-generation sequencing with the MiSeq® System enables researchers to study the microbiotaof humans, model organisms, and clinical environments.
Introduction
We are never really alone. Each of us is a host to flourishing
populations of microorganisms arranged in communities referred tocollectively as microbiota. Researchers are finding that regardless ofwhether they’re located in the gut, skin, or airways, these communities
possess great diversity that can change as we age, in response tocertain diseases, changes in diet, or the ingestion of therapeutic drugs.
While some pathogenic microorganisms can lead to disease or evendeath, many are essential to human health and well-being.
New microbial profiling approaches, such as 16S ribosomal RNA(rRNA) sequencing on the MiSeq System, have led to a greater
understanding of our microbial communities and their interactions withus. Christopher Taylor, PhD, is part of the Louisiana State University
Health Science Center (LSUHSC) Microbial Genomics Resource
Group, an organization that supports microbial genomics with
scientific expertise and research services. As an Associate Professor
in the Department of Microbiology, Immunology, and Parasitology, Dr.
Taylor uses rRNA and DNA sequencing approaches to investigate
microbes of importance to human health.
iCommunity spoke with Dr. Taylor about his microbiome projects andhow the MiSeq System has enabled his studies.
Q: How did you become involved in metagenomic studies?
Christopher Taylor (CT): I have a computer science and mathematics
background and got involved with computational biology when I
was in graduate school, where I was part of the US National Human
Genome Research Institute’s Encyclopedia of DNA Elements(ENCODE) project1-3. I began my career as a faculty member at theUniversity of New Orleans by focusing on applying high-throughput
DNA and RNA sequencing in biological studies. One of my early
projects was in collaboration with Dr. Erik Flemington, a virologist at
Tulane University. We became interested in the RNA sequence reads
from human cancer cell lines that did not map back to the humangenome. In many labs at the time, the typical workflow was to map
as many sequencing reads as possible back to the host genome, andthen discard the remaining 15–20% of the reads. We wanted to look
more closely at the nonmapping reads to see if we could find any viral,bacterial, or other recognizable sequences.4-6 This is still an active
collaboration, and our most recent paper shows that there is a lot of
microbial contamination in existing RNA sequencing data sets.7
Now that I’m at the LSUHSC School of Medicine, there’s more of ahealth care focus to my work, and I’ve become immersed in researchon microbial communities. My primary focus over the last 4 years
has been using 16S rRNA sequencing to study the different microbialFor Research Use Only. Not for use in diagnostic procedures.

communities that populate model organisms, humans, and theenvironments in which they live.
Q: What microbiomes are you studying?
CT: We have various ongoing studies looking at gut, vaginal, airway,
and environmental microbiota. In a recent collaborative research study
with Drs. Michael Ferris and Duna Penn at Children’s Hospital of New
Orleans, we used sequencing to look at the gut microbiota of infants inthe neonatal intensive care unit, particularly premature infants sufferingfrom necrotizing enterocolitis.8-9 Using 16S rRNA sequencing, wefound that these infants have altered fecal microbiota characterized bya very low diversity in gut microbial communities, which might makethem more susceptible to developing necrotizing enterocolitis.
Q: Have any of your studies looked at how diet impacts thegut microbiome?
CT: We’ve performed several studies where we’ve used sequencing to
identify diet-associated variations in the gut microbiomes of mice.10-11
In a recent collaborative study with Drs. Hans-Rudolf Berthoud,
Annadora Bruce-Keller, Michael Salbaum, and David Welsh, we
performed an antibiotic knockdown of the microbial gut community
in a group of mice that had been on a standard mouse chow diet. By
oral gavage, we then transplanted in the microbiota from mice that
had been fed either a high-fat diet (HFD) or a standard mouse chow
diet. Sequencing-based phylogenetic analysis using the MiSeq System
confirmed the presence of a very distinctive difference in microbiota
between the groups. The mice given HFD microbiota also showedChristopher Taylor, PhD is an Associate Professor at theLouisiana State University Health Sciences Center.

May 2015
significant and selective differences in laboratory measures of mouse
behavior, such as fear conditioning, maze solving, and anxiety display.
This data reinforced the link between gut dysbiosis and obesityassociated changes in neurocognitive behavior in mice.

Sequencing-based phylogenetic
analysis using the MiSeq System
confirmed the presence of a very
distinctive difference in microbiota
between the groups.
Q: What other microbiome studies have you performed that enabled
you to see the impact that microbiomes have on disease?
CT: We have conducted several genitourinary tract studies incollaboration with Drs. David Martin and Michael Ferris at LSUHSC.
In one study, we looked at a disease called bacterial vaginosis andthe role of Gardnerella vaginalis, which was originally thought to be
the etiologic agent for that disease. A recent paper had shown that
there are 2 fundamental G. vaginalis genotypes, a biofilm-forming
pathogenic variant that was found in all patients with BV, and acommensal variant that does not form biofilms.12
In our study, we obtained samples from 53 women and their malesexual partners and used 16S rRNA sequencing to investigate the2 G. vaginalis genotypes and their impact on disease.13 During thatinvestigation, a graduate student in my lab, Murat Eren, developed anew method called oligotyping that allowed us to differentiate between
various G. vaginalis strains based only on 16S sequencing data.
Dr. Martin had observed a phenomenon in the clinic where women
diagnosed with bacterial vaginosis would finish a course of antibiotics,and be cured, but would then return to the clinic several weeks
later with the same symptoms. Our idea was that the bacteria wereharbored by the male sexual partner and transmitted back to thewoman during sexual activity following the completion of antibiotictreatment. When we looked at the bacterial 16S oligotyping profiles of
G. vaginalis from the women and men in the study, we found that wecould determine which participants were sexual partners, without apriori knowledge and with a high degree of certainty. The ability to lookthis deeply into strain level variation using only 16S rRNA sequencing
was unprecedented and has since been extended with a method
called Minimum Entropy Decomposition by Murat and his colleagues
and applied to several interesting microbial community studies.14
Q: What is the value of 16S sequencing?
CT: 16S sequencing enables us to identify bacterial species present
in a community and to separate similar strains using techniques
like oligotyping. We’re currently working on an airway study incollaboration with Dr. David Welsh where we’re using 16S sequencing
data to look at relatively subtle differences between microbiota
sampled from the oral cavity with microbiota from tissue samples
taken further down the airway with different sampling brushes.
Compared to gut microbiota, the bacterial burden of airway microbiota
is a lot lower. The further down the airway you go, the fewer bacteria
you will find. We want to determine how these microbiota transit

For Research Use Only. Not for use in diagnostic procedures.

between these different environments and what this might tell us about
the composition of microbiota living deeper in the airways.
Q: What types of environmental microbiome studies areyou performing?
CT: We are planning a 16S sequencing study using the MiSeq System
to analyze the metagenomic landscape of the Intensive Care Units(ICUs) in the new University Medical Center that is scheduled toopen in mid-2015. We’re very interested in looking at environmental
samples from the new trauma ICU and medical ICU before patientsare moved in and as these ICUs are put into service. Based on a trial
run in another operating medical facility using qPCR to quantify 16S
ribosomal RNA, we found the largest microbial counts came fromthe floor and from the lever on the hand sanitizer. In the new medicalcenter, we’re proposing to sample patient rooms and common areas
where health care workers will be walking and using equipment, suchas computer terminals, hand sanitizers, and scanners for tracking
drug administration.
We also want to look at how antibiotic-resistant organisms end
up entering and moving around in these new ICUs. One of ourcollaborators on the study is proposing a simultaneous culture-based
investigation to look for particular antibiotic-resistant organisms. We’rehoping to associate our 16S sequencing data with antibiotic-resistantand nonresistant versions of the cultured microorganisms and better
understand how to control and prevent the spread of antibioticresistant microorganisms.
Q: What types of sequencing approaches did you use before
obtaining a MiSeq System?
CT: In some of my initial research, we used genome tiling microarrays,
but by the mid-2000s they had become obsolete with the advent ofhigh-throughput sequencing. When I arrived at LSU, the School ofMedicine had a pyrosequencing system that was being used to obtainlong read lengths for 16S rRNA studies. This pyrosequencing system
was older technology and was fraught with problems due to the large
number of complex steps required for sample preparation. On manyoccasions, we struggled with this technology and had to perform
multiple repeated sequencing runs attempting to resolve questionable
results. It was also a long process, when you consider the timerequired for sample preparation, sequencing, and the weeks-long,intensive computation that was required to de-noise and prepare thedata for analysis.
Q: How has the MiSeq System improved your workflow?
CT: We obtained a MiSeq System in August 2013, and the difference
was like night and day. The cartridge-based MiSeq System eliminatedmany sources of variation where things could go wrong in sequencing
preparation. Our sequencing throughput has been reduced fromweeks to days. Due to the consistent and high-quality data generated
by the MiSeq System, we were able to move forward with severalof our projects. We didn’t have to go back and repeat the same
sequencing run over and over, trying to get usable data.
For our first MiSeq sequencing run, we used samples from themouse gut repopulation study I mentioned earlier. When we ran thesesamples on the MiSeq System, the results were some of the best data
we had ever seen. The beta diversity plot groupings obtained for theHFD mice versus the control diet mice were incredibly distinct andprovided a better separation than we could have expected. We wereMay 2015
even able to identify a mislabeled sample from the study due to theextremely high fidelity of the diet groupings.

The cartridge-based MiSeq
System eliminated many sourcesof variation where things could gowrong in sequencing preparation.
Q: What do you see for the future of metagenomics?
CT: One thing I envision is the prescriptive use of probiotics. Currently,
there is a lot of pseudoscience in the supplement industry, promoting
probiotics that are just different strains of Lactobacillus. The market
for these products is based on the idea that Lactobacillus is generally
helpful as a way to improve or maintain human health. Sequencing
approaches will enable us to acquire a much more nuanced andspecific understanding of what a healthy gut microbial community isand what kinds of treatments are possible, and the benefits of certainprobiotics. Similar to the promise of personalized medicine, I think thatin the future, we’ll be able to determine a person’s gut microbiota andthe kinds of probiotics that could be most beneficial for them. That issomething I see on the long-term horizon for microbiome research.

References
1.

ENCODE Project Consortium. The ENCODE (ENCyclopedia Of DNA
Elements) Project. Science. 2004; 306(5696): 636–640.
2. Kamani N, Taylor C, Malhotra A, Dutta A. Pan-S replication patterns
and chromosomal domains defined by genome-tiling arrays of ENCODE
genomic areas. Genome Res. 2007; 17(6): 865–876.
3. ENCODE Project Consortium. Identification and analysis of functionalelements in 1% of the human genome by the ENCODE pilot project.
Nature. 2007; 447(7146): 799–816.
4. Lin Z, Puetter A, Coco J, et al. Detection of murine leukemia virus in theEpstein-Barr virus-positive human B-cell line, using a computational RNASeq-based exogenous agent detection pipeline, PARSES. J Virol. 2012;
86(6): 2970–2977.
5. Strong MJ, O’Grady T, Lin Z, et al. Epstein-Barr virus and human herpes
virus 6 detection in a non-Hodgkin’s diffuse large B-cell lymphoma cohort byusing RNA sequencing. J Virol. 2013; 87(23): 13059–13062.
6. Xu G, Strong MJ, Lacey MR, Baribault C, Flemington EK, Taylor CM. RNA
CoMPASS: a dual approach for pathogen and host transcriptome analysisof RNA-Seq data sets. PloS One. 2014; 9(2): e89445.
7. Strong MJ, Xu G, Morici L, et al. Microbial contamination in next generation
sequencing: implications for sequence-based analysis of clinical samples.
PloS Pathog. 2014; 10(11): e1004437.
8. Gupta RW, Tran L, Norori J, et al. Histamine-2 receptor blockers alter thefecal microbiota in premature infants. J Pediatr Gastroenterol Nutr. 2013;
56(4): 397–400.
9. McMurtry VE, Gupta RW, Tran L, et al. Bacterial diversity and Clostridia
abundance decrease with increasing severity of necrotizing enterocolitis.
Microbiome. 2015; 3:11 doi: 10.1186 /s40168-015-0075-8.
10. Wicks S. Taylor CM, Luo M, et al. Artemisia supplementation differentiallyaffects the mucosal and lumenal ileal microbiota of diet-induced obese mice.
Nutrition. 2014: 30(7-8 Suppl): S26-30. Doi: 10.1016/j.nut.2014.02.007.
11. Bruce-Keller AJ, Salbaum JM, Luo M, et al. Obese-type Gut Microbiota
Induce Neurobehavioral Changes in the Absence of Obesity. Biol Psychiatry.
2015; 77(7): 607–615.

For Research Use Only. Not for use in diagnostic procedures.

12. Harwich MD Jr, Alves JM, Buck GA, et al. Drawing the line between
commensal and pathogenic Gardnerella vaginalis through genome analysis
and virulence studies. BMC Genomics. 2010; 11:375 doi: 10.1186/14712164-11-375.
13. Eren AM, Zosaya M, Taylor CM, Dowd SE, Martin DH, Ferris MJ. Exploring
the diversity of Gardnerella vaginalis in the genitourinary tract microbiota ofmonogamous couples through subtle nucleotide variation. PloS One. 2011;
6(10): e26732.
14. Eren AM, Morrison HG, Lescault PJ, Reveillaud J, Vineis JH, Sogin ML.
Minimum entropy decomposition: Unsupervised oligotyping for sensitive
partitioning of high-throughput marker gene sequences. ISME J. 2015;
9:968–979.

Learn more about the Illumina system mentioned
in this article:•MiSeq System, www.illumina.com/systems/miseq.html

May 2015

Illumina • 1.800.809.4566 toll-free (US) • +1.858.202.4566 tel • techsupport@illumina.com • www.illumina.com
For Research Use Only. Not for use in diagnostic procedures.
© 2015 Illumina, Inc. All rights reserved. Illumina, MiSeq, and the pumpkin orange color are trademarks of Illumina, Inc. and/or its affiliate(s)in the U.S. and/or other countries. Pub. No. 1270-2015-002 Current as of 14 May 2015