Microbial 16S rRNA Ion Tag and community metagenome sequencing using the Ion Torrent (PGM) Platform

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Abstract

Here we demonstrate a cost effective and scalable microbial ecology sequencing platform using the Ion Torrent Personal Genome Machine (PGM). We assessed both PCR amplified 16S rRNA and shotgun metagenomic approaches and generated 100,000 + to 1,000,000 + reads using ‘post-light’ based sequencing technology within different sized semi-conductor chips. Further development of Golay barcoded Ion Tags allowed multiplex analyses of microbial communities with substantially reduced costs compared with platforms such as 454/GS-FLX. Using these protocols we assessed the bacterial and archaeal dynamics within covered anaerobic digesters used to treat piggery wastes. Analysis of these sequence data showed that these novel methanogenic waste treatment systems are dominated by bacterial taxa, in particular Clostridium, Synergistia and Bacteroides that were maintained as a stable community over extended time periods. Archaeal community dynamics were more stochastic with the key methanogenic taxa more difficult to resolve, principally due to the poor congruence seen between community structures generated either by nested PCR or metagenomic approaches for archaeal analyses. Our results show that for microbial community structure and function analyses, the PGM platform provides a low cost, scalable and high throughput solution for both Tag sequencing and metagenomic analyses.

Highlights

► ‘Post light’ DNA sequencer producing analyses in 8 hours with low reagent costs ► Scalable chip based sequencing ranging from 100,000 to 1,000,000 + reads ► Multiplex 16S rRNA analyses developed and demonstrated in anaerobic digesters. ► Novel covered anaerobic ponds dominated by Bacteroidia, Synergistia and Clostridia.

Introduction

Over the past 10 years our understanding of microbial diversity and function in complex environments has increased significantly. This is primarily a result of the introduction of next generation sequencing (NGS) (Lozupone and Knight, 2007, Sogin et al., 2006). Both PCR based analysis of 16S rRNA and shotgun metagenomic studies have been used recently to characterise soils (Fierer et al., 2011), oceans (Caporaso et al., 2011), the atmosphere (Bowers et al., 2011) as well as the human microbiome (Kuczynski et al., 2011). Prior to the advent of NGS, the high throughput genetic analysis of complex microbial community samples was only possible using low resolution ‘fingerprinting’ technologies e.g. (Griffiths et al., 2011) or Sanger sequencing at extremely high cost e.g. (Rusch et al., 2007). However, with NGS we now have the potential to fully sequence, at high taxonomic resolution, most known habitats on Earth (Gilbert et al., 2010).

At the vanguard of this revolution in microbial ecology are core and ancillary technological advances that have enabled the high throughput solutions essential for studying microbial community dynamics and function. These include the original pyrosequencing developments for high throughput sequence generation (Margulies et al., 2005), developments in multiplex analyses through barcoding (Hamady et al., 2008), step changes in sequence outputs to ultra-high throughput systems (Bartram et al., 2011, Caporaso et al., 2012) and substantial increases in the ability to analyse and handle data outputs (Caporaso et al., 2010, Lozupone and Knight, 2005, Meyer et al., 2008).

Until relatively recently, a number of factors have limited the uptake of large scale sequencing capabilities within personal laboratories. These include the need for ‘facility’ level support for technically complex platforms and the need for large initial equipment purchase and ongoing analysis costs (Glenn, 2011). Further, in many cases a factor best termed the ‘fixed system issue’ means that many existing NGS technologies depend on key, but fixed, light detection systems. Thus, as technology improves, flexible upgrades on detection systems are rare and new sequencing platforms have to be purchased to keep pace with new NGS developments and increased outputs (Glenn, 2011). These factors prevent many small to medium laboratories from adopting existing high throughput technologies ‘in house’ and rely instead on central facilities. This is a particular problem for many microbial ecology laboratories where the need for replication and longitudinal studies means relatively high outsource costs and results in a situation where routine access to the technology is reduced. However, the availability of low cost, high throughput systems would add value to existing ‘facility’ based environmental sequencing efforts and to the ‘democratisation’ of sequencing for the good of global microbial ecology (Caporaso et al., 2012).

Recently, a different strategy of ‘ion’ sequencing, commercially available within the Ion Torrent Personal Genome Machine (PGM) (Life Technologies), has received considerable attention. PGM sequencing is light independent where sequence composition is determined by measuring pH changes due to hydrogen ion liberation as nucleotides are incorporated during strand synthesis in picolitre wells (Rothberg et al., 2011). Using integrated circuits to measure pH changes to identify base incorporation removes the need for expensive light detection systems, substantially reduces costs and, theoretically, is infinitely scalable; since the number of sequences obtained simply equates to the physical dimensions of the integrated sensor (Glenn, 2011). However, since the PGM is a relatively new technology, and approaches sequencing in a different way to standard NGS platforms, there has been much speculation as to the suitability of the platform for microbial ecology. This includes the quality and extent of the output (the number and read length of sequences) as well as the compatibility with downstream data analysis pipelines and the ability to multiplex microbial community analyses.

To address these questions we have investigated PGM sequencing for microbial ecology and examined bacterial and archaeal community dynamics in a covered anaerobic pond (CAP) used to treat piggery waste. CAPs represent a novel and low cost option for treating effluent ponds and are being used to provide a cost effective anaerobic digester by covering the ponds with a geosynthetic material. CAP systems have the benefits of renewable energy generation via biologically mediated methanogenesis (with concomitant GHG mitigation). Here, we have developed the PGM sequencing protocols and used these to investigate the community structures, temporal stability and major taxa of these CAP systems.

Section snippets

Site description, sampling and DNA extractions

A covered anaerobic pond (CAP) at Medina Research Station (MRS), Western Australia (GPS geocoder: latitude − 32.223000, longitude 115.805801) was used as the source of samples to investigate both the microbial production of methane by anaerobic digestion of piggery waste and the efficacy of community structure analyses using PGM sequencing. Effluents from pig holding pens were collected and solids were mechanically screened and removed prior to transferring the remaining wastewater into a

Read output and base positional quality from 314 and 316 PGM Chips

We first sought to quantify the absolute number of PCR amplified 16S rRNA sequence read outputs and to categorise those reads of sufficient quality for downstream phylogenetic analyses, from both 314 (10 Mb.p) and 316 (100 Mb.p) PGM chips. For both the 314 and 316 chips we assessed the total number of reads generated (as a proxy for active sequencing wells on each chip) and demonstrated that the mean raw read output exceeded 650,000 reads for 314 chips (manufacturer specifies a minimum output of

Scalable sequence output

The Ion Torrent PGM platform is currently one of the lowest cost next generation sequencers capable of multi-million read level outputs. Further, through the use of ‘post-light’ chemical sensor technology, sequence outputs can be scalable through different chip sensor sizes and allows sequence turnaround times of only a few hours (Glenn, 2011). Utilising different output PGM chips we routinely generated an average of ca. 350,000 (314 PGM chip) or 1.2 million reads (316 PGM chip) within 8 h. These

Acknowledgements

This work was funded by grants from Australia Pork Ltd and the Australian Grains Research and Development Corporation (GRDC), from UWA and the Vice Chancellor's Discretionary Fund and through the core science budget of CEH to support the sabbatical visit of ASW to UWA. We thank Jack Gilbert for the advice and sequences relating to the Golay Barcodes, Kelly Ewen-White for the discussions regarding the PGM and Charles Morgan for the provision of the PGM through a charitable donation.

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