Chapter 2.4.2 : Microbial Community Analysis Using High-Throughput Amplicon Sequencing

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The fields of microbial ecology and environmental microbiology have been revolutionized by the development of next-generation sequencing technologies. In this chapter we specifically address the use of PCR amplification coupled with high-throughput sequencing for the analysis of microbial community composition and structure, and for subsequent visualization and statistical analyses of this community data.

Citation: Ionescu D, Overholt W, Lynch M, Neufeld J, Naqib A, Green S. 2016. Microbial Community Analysis Using High-Throughput Amplicon Sequencing, p 2.4.2-1-2.4.2-26. In Yates M, Nakatsu C, Miller R, Pillai S (ed), Manual of Environmental Microbiology, Fourth Edition. ASM Press, Washington, DC. doi: 10.1128/9781555818821.ch2.4.2
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Image of FIGURE 1

. Shown are the Earth Microbiome Project (EMP) primers for amplification and sequencing of the V4 variable region of microbial 16S rRNA genes on the Illumina sequencing platform. doi:10.1128/9781555818821.ch2.4.2.f1

Citation: Ionescu D, Overholt W, Lynch M, Neufeld J, Naqib A, Green S. 2016. Microbial Community Analysis Using High-Throughput Amplicon Sequencing, p 2.4.2-1-2.4.2-26. In Yates M, Nakatsu C, Miller R, Pillai S (ed), Manual of Environmental Microbiology, Fourth Edition. ASM Press, Washington, DC. doi: 10.1128/9781555818821.ch2.4.2
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Image of FIGURE 2

. Shown are the Earth Microbiome Project (EMP) primers with Fluidigm common sequence linkers for amplification and sequencing of the V4 variable region of microbial 16S rRNA genes on the Illumina sequencing platform. Two separate PCR stages are required to generate template-specific amplicons, and to attach sample-specific barcodes and sequencing adapters. doi:10.1128/9781555818821.ch2.4.2.f2

Citation: Ionescu D, Overholt W, Lynch M, Neufeld J, Naqib A, Green S. 2016. Microbial Community Analysis Using High-Throughput Amplicon Sequencing, p 2.4.2-1-2.4.2-26. In Yates M, Nakatsu C, Miller R, Pillai S (ed), Manual of Environmental Microbiology, Fourth Edition. ASM Press, Washington, DC. doi: 10.1128/9781555818821.ch2.4.2
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Image of FIGURE 3

. A basic local alignment search tool (BLAST) analysis was performed to compare the two gene sequences. Mismatches are highlighted in red. The region of comparison begins at the 5′ end of the molecule, directly after the commonly used domain-level primer 27F, and ends just before the commonly used domain-level primer 1492R. Common primer sequences, highlighted in green, include 341F, 534R, 806R, 907R, 1114R, and 1392R (from left to right). Approximate locations of the nine microbial variable regions are indicated. Note that no differences exist between the two sequences in the V4 region, commonly targeted by the 515F/806R primer set. doi:10.1128/9781555818821.ch2.4.2.f3

Citation: Ionescu D, Overholt W, Lynch M, Neufeld J, Naqib A, Green S. 2016. Microbial Community Analysis Using High-Throughput Amplicon Sequencing, p 2.4.2-1-2.4.2-26. In Yates M, Nakatsu C, Miller R, Pillai S (ed), Manual of Environmental Microbiology, Fourth Edition. ASM Press, Washington, DC. doi: 10.1128/9781555818821.ch2.4.2
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Image of FIGURE 4

A single gDNA sample from mammalian feces (chinchilla) was PCR amplified using a two-step PCR protocol, utilizing the EMP primers and Fluidigm common sequence linkers. A systematic variation of first-stage and second-stage PCR cycles was performed, with a range of 20–36 cycles total. After sequencing on an Ion Torrent PGM, sequence data were demultiplexed and chimeras were identified using usearch61. A linear relationship between total cycle number and chimera formation ( = 0.65) was observed. doi:10.1128/9781555818821.ch2.4.2.f4

Citation: Ionescu D, Overholt W, Lynch M, Neufeld J, Naqib A, Green S. 2016. Microbial Community Analysis Using High-Throughput Amplicon Sequencing, p 2.4.2-1-2.4.2-26. In Yates M, Nakatsu C, Miller R, Pillai S (ed), Manual of Environmental Microbiology, Fourth Edition. ASM Press, Washington, DC. doi: 10.1128/9781555818821.ch2.4.2
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Image of FIGURE 5

The number of identified OTUs generated at each similarity threshold is standardized by the number of OTUs identified at 100% similarity (solid line). The percent change in number of OTU at each threshold was also calculated (dashed line) and shows that the greatest change occurs from a 98% to 97% threshold cutoff. The data are derived from six amplicon data sets generated on a Roche 454 pyrosequencer. doi:10.1128/9781555818821.ch2.4.2.f5

Citation: Ionescu D, Overholt W, Lynch M, Neufeld J, Naqib A, Green S. 2016. Microbial Community Analysis Using High-Throughput Amplicon Sequencing, p 2.4.2-1-2.4.2-26. In Yates M, Nakatsu C, Miller R, Pillai S (ed), Manual of Environmental Microbiology, Fourth Edition. ASM Press, Washington, DC. doi: 10.1128/9781555818821.ch2.4.2
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Image of FIGURE 6

. A consistent decrease in the number of measured OTUs was observed when sample diversity was estimated based on total data set clustering as opposed to one-by-one sample clustering and diversity calculations. The four data sets, from freshwater (DB1), seawater (DB2), marine sediments (DB3), and microbial mats (DB4), consisted of 10–40 samples each, with amplicons generated on a Roche 454 pyrosequencer. doi:10.1128/9781555818821.ch2.4.2.f6

Citation: Ionescu D, Overholt W, Lynch M, Neufeld J, Naqib A, Green S. 2016. Microbial Community Analysis Using High-Throughput Amplicon Sequencing, p 2.4.2-1-2.4.2-26. In Yates M, Nakatsu C, Miller R, Pillai S (ed), Manual of Environmental Microbiology, Fourth Edition. ASM Press, Washington, DC. doi: 10.1128/9781555818821.ch2.4.2
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