Comparing Apples and Oranges?: Next Generation Sequencing and Its Impact on Microbiome Analysis

Clooney, Adam G.; Fouhy, Fiona; Sleator, Roy D.; Driscoll, Aisling O‘; Stanton, Catherine; Cotter, Paul D.; Claesson, Marcus J.

doi:10.1371/journal.pone.0148028

Cited by 231 publications

(215 citation statements)

References 38 publications

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“…Presence of sulfur sediments Crenarchaeota (Desulfurococcales, Thermoproteales) (Inskeep et al 2013a) (Inskeep et al 2013b) 16 CIS Crenarchaeota (Desulfurococcales, Thermoproteales) (Inskeep et al 2013a) (Inskeep et al 2013b) be used to test-run sequencing libraries before analysis on HiSeq instruments, deeper sequencing is strictly required in order to detect the majority of species in a sample and to perform an high quality assembly with a good abundance estimation of the microorganisms (Clooney et al 2016).…”

Section: Nr Low Dissolved Oxygen Concentrationmentioning

confidence: 99%

Metagenomics of microbial and viral life in terrestrial geothermal environments

Strazzulli

Fusco

Cobucci‐Ponzano

et al. 2017

Rev Environ Sci Biotechnol

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Geothermally heated regions of Earth, such as terrestrial volcanic areas (fumaroles, hot springs, and geysers) and deep-sea hydrothermal vents, represent a variety of different environments populated by extremophilic archaeal and bacterial microorganisms. Since most of these microbes thriving in such harsh biotopes, they are often recalcitrant to cultivation; therefore, ecological, physiological and phylogenetic studies of these microbial populations have been hampered for a long time. More recently, culture-independent methodologies coupled with the fast development of next generation sequencing technologies as well as with the continuous advances in computational biology, have allowed the production of large amounts of metagenomic data. Specifically, these approaches have assessed the phylogenetic composition and functional potential of microbial consortia thriving within these habitats, shedding light on how extreme physico-chemical conditions and biological interactions have shaped such microbial communities. Metagenomics allowed to better understand that the exposure to an extreme range of selective pressures in such severe environments, accounts for genomic flexibility and metabolic versatility of microbial and viral communities, and makes extreme-and hyper-thermophiles suitable for bioprospecting purposes, representing an interesting source for novel thermostable proteins that can be potentially used in several industrial processes.Keywords Hyperthermophiles Á Geothermal environments Á Microbial and viral metagenomics Á CRISPR Á Enzyme discovery BackgroundHot springs populated by extreme thermophiles (T opt : 65-79°C) and hyperthermophiles (T opt [ 80°C) (DeCastro et al. 2016) are very diverse and some of them show combinations of extreme chemo-physical conditions, such as temperature, acidic or alkaline pHs, high pressure, and high concentrations of salts and heavy metals (López-López et al. 2013). As with all studies of environmental microbiology, our understanding of the composition, functional and physiological dynamics, and evolution of extreme-and hyper-thermophilic microbial consortia has lagged A. Strazzulli Á M. Moracci Á P. Contursi

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Section: Nr Low Dissolved Oxygen Concentrationmentioning

confidence: 99%

Metagenomics of microbial and viral life in terrestrial geothermal environments

Strazzulli

Fusco

Cobucci‐Ponzano

et al. 2017

Rev Environ Sci Biotechnol

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“…DNA extracts were quantified using the Qubit high-sensitivity DNA assay (BioSciences, Dublin, Ireland), and 16S rRNA gene sequencing libraries were prepared from extracted DNA using the 16S metagenomic sequencing library preparation protocol from Illumina, with minor modifications (36). Samples were sequenced on the Illumina MiSeq system in the Teagasc sequencing facility with a V2 kit (2 ϫ 250 cycles), in accordance with standard Illumina sequencing protocols.…”

Section: Microbiological Analysismentioning

confidence: 99%

“…Samples were sequenced on the Illumina MiSeq system in the Teagasc sequencing facility with a V2 kit (2 ϫ 250 cycles), in accordance with standard Illumina sequencing protocols. Whole-metagenome shotgun libraries were prepared in accordance with the Nextera XT DNA library preparation guide from Illumina (36). Samples were sequenced on the Illumina MiSeq system in the Teagasc sequencing facility with a V3 kit (2 ϫ 300 cycles), in accordance with standard Illumina sequencing protocols.…”

Section: Microbiological Analysismentioning

confidence: 99%

Strain-Level Metagenomic Analysis of the Fermented Dairy Beverage Nunu Highlights Potential Food Safety Risks

Walsh

Crispie

Daari

et al. 2017

Appl Environ Microbiol

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The rapid detection of pathogenic strains in food products is essential for the prevention of disease outbreaks. It has already been demonstrated that whole-metagenome shotgun sequencing can be used to detect pathogens in food but, until recently, strain-level detection of pathogens has relied on wholemetagenome assembly, which is a computationally demanding process. Here we demonstrated that three short-read-alignment-based methods, i.e., MetaMLST, PanPhlAn, and StrainPhlAn, could accurately and rapidly identify pathogenic strains in spinach metagenomes that had been intentionally spiked with Shiga toxin-producing Escherichia coli in a previous study. Subsequently, we employed the methods, in combination with other metagenomics approaches, to assess the safety of nunu, a traditional Ghanaian fermented milk product that is produced by the spontaneous fermentation of raw cow milk. We showed that nunu samples were frequently contaminated with bacteria associated with the bovine gut and, worryingly, we detected putatively pathogenic E. coli and Klebsiella pneumoniae strains in a subset of nunu samples. Ultimately, our work establishes that short-read-alignmentbased bioinformatics approaches are suitable food safety tools, and we describe a real-life example of their utilization.IMPORTANCE Foodborne pathogens are responsible for millions of illnesses each year. Here we demonstrate that short-read-alignment-based bioinformatics tools can accurately and rapidly detect pathogenic strains in food products by using shotgun metagenomics data. The methods used here are considerably faster than both traditional culturing methods and alternative bioinformatics approaches that rely on metagenome assembly; therefore, they can potentially be used for more high-throughput food safety testing. Overall, our results suggest that wholemetagenome sequencing can be used as a practical food safety tool to prevent diseases or to link outbreaks to specific food products.KEYWORDS fermentation, food-borne pathogens, metagenomics I n recent years, high-throughput sequencing (HTS) has become an important tool in food microbiology (1). HTS enables in-depth characterization of food-related microbial isolates, via whole-genome sequencing (WGS), and it facilitates cultureindependent analysis of mixed microbial communities in foods, via metagenomic sequencing.WGS has provided invaluable insights into the genetics of starter cultures (2, 3), and it is routinely used in epidemiology to identify outbreak-associated foodborne pathogens isolated from clinical samples, through comparison of the single-nucleotide polymorphism (SNP) profiles of outbreak strain genomes versus nonoutbreak strain

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“…A large body of work in the field has addressed day-to-day operations (38) involved in performing microbiome studies in research and epidemiological settings (39,40) including sample collection and storage (41)(42)(43), laboratory protocols for sample processing (40,44), choice of microbiome sequencing protocols (45) and the computational infrastructure required for data processing and storage (46,47). This review builds on these discussions while specifically focusing on the design of translational microbiome studies and development of downstream statistical analysis plans which answer complex questions in a translational setting and inform early and late-phase clinical trials.…”

Section: Introduction: the Microbiome In Translational Medicinementioning

confidence: 99%

Insights into study design and statistical analyses in translational microbiome studies

Shankar¹

2017

Ann. Transl. Med.

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Research questions in translational microbiome studies are substantially more complex than their counterparts in basic science. Robust study designs with appropriate statistical analysis frameworks are pivotal to the success of these translational studies. This review considers how study designs can account for heterogeneous phenotypes by adopting representative sampling schemes for recruiting the study population and making careful choices about the control population. Advantages and limitations of 16S profiling and whole-genome sequencing, the two primary techniques for measuring the microbiome, are discussed followed by an overview of bioinformatic processing of high-throughput sequencing data from these measurements. Practical insights into the downstream statistical analyses including data processing and integration, variable transformations, and data exploration are provided. The merits of regularization and ensemble modeling for analyzing microbiome data are discussed along with a recommendation for selecting modeling approaches based on data-driven simulations and objective evaluation. The review builds on several recent discussions of study design issues in microbiome research but with a stronger emphasis on the downstream and often-ignored aspects of statistical analyses that are crucial for bridging the gap between basic science and translation.

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Comparing Apples and Oranges?: Next Generation Sequencing and Its Impact on Microbiome Analysis

Cited by 231 publications

References 38 publications

Metagenomics of microbial and viral life in terrestrial geothermal environments

Metagenomics of microbial and viral life in terrestrial geothermal environments

Strain-Level Metagenomic Analysis of the Fermented Dairy Beverage Nunu Highlights Potential Food Safety Risks

Insights into study design and statistical analyses in translational microbiome studies

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