Application Note: Microbial Genomics

Metagenomic Analysis of Environmental
Water Samples With the NextSeq 500 System®

Shotgun metagenomic sequencing provides insight into microbial responses to environmental
changes in a water reservoir.
Introduction

Methods

Environmental metagenomics is the study of organisms in a microbialcommunity by analyzing the DNA present in an environmental
sample. The advent of next-generation sequencing (NGS) technology
has enabled researchers to profile entire microbial communities incomplex samples quickly and easily. Unlike capillary electrophoresis
or PCR, NGS allows investigators to sequence thousands oforganisms in parallel. With shotgun metagenomic sequencing,
microbiologists can examine the genes of the organisms in a given
sample comprehensively to evaluate bacterial diversity and detectmicrobial abundance in various environments. When designing a
shotgun metagenomic sequencing study, researchers must consider
many factors, including the complexity of the sample and thesequencing output required to assess microbial diversity. Illumina
library preparation kits and the NextSeq Series of sequencing systems
delivers the efficiency, high throughput, speed, and sample size
flexibility needed for efficient and affordable metagenomics studies.
This application note describes how investigators from the Center
for Earth and Environmental Science and Indiana University-Purdue
University Indianapolis (IUPUI) used shotgun metagenomic sequencing
to characterize microbial communities in samples from the Eagle
Creek reservoir in Indianapolis, Indiana. The method includes sample
collection, DNA extraction using the Meta-G-NomeTM DNA Isolation
Kit,1 DNA library preparation with the Nextera® XT DNA Library Prep
Kit,2 sequencing with the NextSeq 500 System,3 and analysis using
the MG-RAST metagenomics analysis server4 (Figure 1). The resultspresented in this study provide new insights into the taxonomic andfunctional differences between microbial communities in the Eagle
Creek drinking water supply reservoir at different times and locations.

Sample Extraction

Library Preparation

Sample Collection
In collaboration with Citizens Water Company,5 the Center for Earthand Environmental Science (IUPUI) regularly samples, monitors, anddocuments the water supply in the Eagle Creek reservoir. The samples
for this study were collected at regular intervals, from May to October
2013, before the first frost. Discrete samples were collected from thesurface, and at the depths of 3 meters, 6 meters, and near the bottom
floor of the reservoir. During the sampling process, 150 ml of lakewater were collected, filtered through a 0.22 μm filter, and frozen
at -20°C.

Genomic DNA Isolation
After sample collection, DNA was isolated directly from the water
sample using the Meta-G-Nome DNA Isolation Kit (Epicentre®,an Illumina company). The protocol uses filtration technology andenzymatic lysis to isolate DNA from the water sample. The kit
is designed to isolate randomly sheared genomic DNA of highmolecular weight.

Library Preparation
The Nextera XT DNA Library Prep Kit was used to construct libraries
from the isolated DNA. Using a single enzymatic “tagmentation”
reaction, the Nextera transposome simultaneously fragmented andtagged the DNA with unique adapter sequences. Limited-cycle PCR
was used to amplify the tagged DNA and add sequencing indexes.
Using this streamlined workflow, 11 DNA libraries were prepared forsequencing on the NextSeq 500 desktop sequencer in half a day.

Sequencing

AnalysisFigure 1: Shotgun Metagenomic Sequencing Workflow—The speed of the Nextera XT DNA Library Prep Kit and the output of the NextSeq Series contribute to afast and efficient workflow suited to NGS-based environmental metagenomics studies.

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

Application Note: Microbial Genomics
Sequencing

Table 1: Sequencing DataMetagenome
Name

Base Counta

Sequence
Countb4554374.3

1305-530

5,061,868,863

33,395,2024554375.3

1305-531

5,566,909,825

37,789,429

4554376.3

1305-532

8,409,674,88557,196,837

4554377.3

1305-533

4,341,474,376

31,003,711

4554378.3

1307-521

5,184,242,473

32,673,383

4554379.3

1307-522

14,173,422,835

85,796,130

Data Analysis

4554380.3

1307-523

8,369,469,023

52,993,984

Data analysis is often the most challenging part of a metagenomic
sequencing study. Several programs and pipelines are available toperform metagenomic analysis. These programs are optimized fordifferent study objectives, such as taxonomic profiling, assessing
microbial composition, or identifying functional genes and pathways.

4554381.3

1307-524

2,864,009,160

19,306,387

4554382.3

1310-522

8,688,763,557

55,503,302

4554383.3

1310-523

10,943,344,357

69,814,786

4554384.3

1310-524

7,776,089,825

46,838,779

All 11 libraries were pooled together for cluster generation andsequencing. Libraries were loaded onto a reagent cartridge andclustered on the NextSeq 500 System. A paired-end, 2 × 150 bp
sequencing run was performed using the NextSeq 500 High-Output
Kit. A single sequencing run generated 400 million reads in 29 hours,
corresponding to an average of 40 million reads per sample after
quality filtering (Table 1). Base calls generated by the NextSeq 500
System were converted to FASTQ files for metagenomic analysis.

The analysis presented in this study used the publicly available
MG-RAST program, an automated analysis platform that provides
various tools for data visualization enabling users to assess species
composition or functional abundance. FASTQ files generated by theNextSeq 500 System and sample metadata (Table 2) were uploaded
to the MG-RAST server. Overlapping paired-end reads were joined
and then processed in MG-RAST using the default trimming andfiltering settings to allow comparison to other data sets in MG-RAST.

MG-RAST ID

a. All sequenced bases
b. Number of sequencing reads

Table 2: Environmental Metadata

Sampling Depth

Sampling Date

Water
Temperature(oC)pH

Air Temperature (oC)

Location
Coordinatesa

Salinity(ppm)

4554374.3

Surface

23 May 2013

21.05

8.72

13.3

39.827, -86.303

0.214554375.3

3 meters

23 May 2013

21.00

8.73

13.3

39.827, -86.303

0.214554376.3

6 meters

23 May 2013

13.77

8.27

13.3

39.827, -86.303

0.224554377.3

Floor

23 May 2013

10.78

7.50

13.3

39.827, -86.303

0.204554378.3

Surface25 July 2013

26.50

8.48

18.9

39.826, -86.304

0.214554379.3

3 meters

25 July 2013

26.02

8.40

18.9

39.826, -86.304

0.234554380.3

6 meters

25 July 2013

23.03

7.60

18.9

39.826, -86.304

0.22

MG-RAST ID

4554381.3

Floor

25 July 2013

13.86

7.16

18.9

39.826, -86.304

0.234554382.3

3 meters

23 October 2013

15.09

7.80

4.4

39.826, -86.304

0.244554383.3

6 meters

23 October 2013

15.06

7.72

4.4

39.826, -86.304

0.244554384.3

Floor

23 October 2013

14.99

7.68

4.4

39.826, -86.304

0.24

a. Global Positioning System (GPS) coordinates

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

Application Note: Microbial Genomics

Arthrobacter
Rhodococcus
Synechococcus
Renibacterium
Clavibacter
Bacillus
Leifsonia
Mycobacterium
Streptomyces
Actinobacteria)

May

Jul MayJul

Oct MayJulOct MayJulOct

Cyanobium
Sanguibacter
Methylobacter
Kocuria
Lysinibacillus

Figure 2: Comparative Genus Abundance Over Time—Comparisons of relative genus abundance (shown for the 15 most abundant genera) demonstrated a sharp
decline in Arthrobacter populations on the reservoir floor in July 2013. These data were generated using MG-RAST.

Results

Learn More

Analysis of species abundance with MG-RAST revealed drasticchanges in microbial composition on the reservoir floor and anincrease in the Rhodococcus genus (a soil bacteria), at the 3 meter
depth in July 2013 (Figure 2). For the reservoir floor, the population
declines might be correlated with an algaecide treatment that occurredon 31 May 2013. It is possible that the copper in the algaecidetreatment caused the sharp decline in species from the Arthrobacter
genus. This hypothesis is based on the observation that Arthrobacter
globiformis often forms a symbiotic relationship with the Anabaena
genus of nitrogen-fixing cyanobacteria and the aquatic ferns in theAzolla genus, both part of the algae family.6 After algaecide treatment,
both Arthrobacter globiformis and Azolla experienced a decline;
however, Azolla is not shown in Figure 2, because it is not 1 of the 15
most abundant genera in the samples. The hypothesis that thegram-positive Anabaena species might have played a role in thechanges to community composition requires further analysis. Likewise
for the 3 meter sampling depth, where analysis revealed an increasein the Rhodococcus genus, further analysis is required to assessroot cause.

To learn more about the NextSeq Series, visit
www.illumina.com/nextseq.

Conclusions
This study demonstrates how shotgun metagenomic sequencing
with the NextSeq 500 System can reveal information about themicrobial composition of a particular environment. The data presented
show a correlation between the environmental metadata and thespecies composition in the Eagle Creek reservoir. This study provides
new insights into the biological processes potentially associatedwith algal blooms, sampling depth, and seasonal differences infreshwater environments.

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

For more information about the use of Illumina technology in microbial
genomics, visit www.illumina.com/microbiology.

References
1.

2.
3.
4.

5.
6.

Meta-G-Nome- DNA Isolation Kit (www.epibio.com/applications/nucleicacid-purification-extraction-kits/dna-purification-genomic/meta-g-nomedna-isolation-kit) Accessed 21 April 2014.
Nextera XT DNA Library Prep Kit (www.illumina.com/products/nextera_xt_dna_sample_prep_kit.ilmn) Accessed 21 April 2014.
NextSeq 500 Desktop Sequencer (www.illumina.com/systems/nextseqsequencer.html) Accessed 21 May 2015.
Meyer F, Paarmann D, D’Souza M, et al. The metagenomics RAST server a public resource for the automatic phylogenetic and functional analysis ofmetagenomes. BMC Bioinformatics. 2008;9:386.
Citizens Energy Group (www.citizensenergygroup.com) Accessed 21
April 2014.
Martens T, Gram L, Grossart HP, et al. Bacteria of the Roseobacterclade show potential for secondary metabolite production. Microb Ecol.
2007;54:31-42.

Application Note: Microbial Genomics

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For Research Use Only. Not for use in diagnostic procedures.
© 2014–2015 Illumina, Inc. All rights reserved. Illumina, Epicentre, Meta-G-Nome, Nextera, NextSeq, and the pumpkin orange color aretrademarks of Illumina, Inc. and/or its affiliate(s) in the U.S. and/or other countries. Pub. No. 1270-2014-002 Current as of 26 May 2015