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Microbial Community Composition and Diversity via 16S rRNA Gene Amplicons: Evaluating the Illumina Platform
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Ecology and Genetics, Limnology. Uppsala University, Science for Life Laboratory, SciLifeLab.
Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Ecology and Genetics, Limnology.
Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Ecology and Genetics, Limnology.
Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Ecology and Genetics, Limnology.
2015 (English)In: PLoS ONE, ISSN 1932-6203, Vol. 10, no 2, e0116955Article in journal (Refereed) Published
Abstract [en]

As new sequencing technologies become cheaper and older ones disappear, laboratories switch vendors and platforms. Validating the new setups is a crucial part of conducting rigorous scientific research. Here we report on the reliability and biases of performing bacterial 16S rRNA gene amplicon paired-end sequencing on the MiSeq Illumina platform. We designed a protocol using 50 barcode pairs to run samples in parallel and coded a pipeline to process the data. Sequencing the same sediment sample in 248 replicates as well as 70 samples from alkaline soda lakes, we evaluated the performance of the method with regards to estimates of alpha and beta diversity. Using different purification and DNA quantification procedures we always found up to 5-fold differences in the yield of sequences between individually barcodes samples. Using either a one-step or a two-step PCR preparation resulted in significantly different estimates in both alpha and beta diversity. Comparing with a previous method based on 454 pyrosequencing, we found that our Illumina protocol performed in a similar manner – with the exception for evenness estimates where correspondence between the methods was low. We further quantified the data loss at every processing step eventually accumulating to 50% of the raw reads. When evaluating different OTU clustering methods, we observed a stark contrast between the results of QIIME with default settings and the more recent UPARSE algorithm when it comes to the number of OTUs generated. Still, overall trends in alpha and beta diversity corresponded highly using both clustering methods. Our procedure performed well considering the precisions of alpha and beta diversity estimates, with insignificant effects of individual barcodes. Comparative analyses suggest that 454 and Illumina sequence data can be combined if the same PCR protocol and bioinformatic workflows are used for describing patterns in richness, beta-diversity and taxonomic composition.

Place, publisher, year, edition, pages
2015. Vol. 10, no 2, e0116955
National Category
Other Natural Sciences
URN: urn:nbn:se:uu:diva-243557DOI: 10.1371/journal.pone.0116955ISI: 000348822600044OAI: oai:DiVA.org:uu-243557DiVA: diva2:787553
Available from: 2015-02-10 Created: 2015-02-10 Last updated: 2016-08-26Bibliographically approved
In thesis
1. Molecular methods for microbial ecology: Developments, applications and results
Open this publication in new window or tab >>Molecular methods for microbial ecology: Developments, applications and results
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Alternative title[en]
Systems approach to functional characterization of lentic systems
Abstract [en]

Recent developments in DNA sequencing technology allow the study of microbial ecology at unmatched detail. To fully embrace this revolution, an important avenue of research is the development of bioinformatic tools that enable scientists to leverage and manipulate the exceedingly large amounts of data produced. In this thesis, several bioinformatic tools were developed in order to process and analyze metagenomic sequence data. Subsequently, the tools were applied to the study of microbial biogeography and microbial systems biology.

A targeted metagenomics pipeline automating quality filtering, joining and taxonomic annotation was developed to assess the diversity of bacteria, archaea and eukaryotes permitting the study of biogeographic patterns in great detail. Next, a second software package which provides annotation based on environmental ontology terms was coded aiming to exploit the cornucopia of information available in public databases. It was applied to resource tracking, paleontology, and biogeography. Indeed, both these tools have already found broad applications in extending our understanding of microbial diversity in inland waters and have contributed to the development of conceptual frameworks for microbial biogeography in lotic systems. The programs were used for analyzing samples from several environments such as alkaline soda lakes and ancient sediment cores. These studies corroborated the view that the dispersal limitations of microbes are more or less non-existant as environmental properties dictating their distribution and that dormant microbes allow the reconstruction of the origin and history of the sampled community.

Furthermore, a shotgun metagenomics analysis pipeline for the characterization of total DNA extraction from the environment was put in place. The pipeline included all essential steps from raw sequence processing to functional annotation and reconstruction of prokaryotic genomes. By applying this tool, we were able to reconstruct the biochemical processes in a selection of systems representative of the tens of millions of lakes and ponds of the boreal landscape. This revealed the genomic content of abundant and so far undescribed prokaryotes harboring important functions in these ecosystems. We could show the presence of organisms with the capacity for photoferrotrophy and anaerobic methanotrophy encoded in their genomes, traits not previously detected in these systems. In another study, we showed that microbes respond to alkaline conditions by adjusting their energy acquisition and carbon fixation strategies. To conclude, we demonstrated that the "reverse ecology" approach in which the role of microbes in elemental cycles is assessed by genomic tools is very powerful as we can identify novel pathways and obtain the partitioning of metabolic processes in natural environments.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2016. 52 p.
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 1388
bioinformatics, microbiology, metagenomics, ecology, metabolism
National Category
Bioinformatics and Systems Biology Ecology
Research subject
urn:nbn:se:uu:diva-297613 (URN)978-91-554-9620-3 (ISBN)
External cooperation:
Public defence
2016-09-08, Friessalen, Evolutionary Biology Center, Norbyvägen 14, Uppsala, 13:15 (English)
Available from: 2016-08-17 Created: 2016-06-24 Last updated: 2016-08-26

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Sinclair, LucasAhmed Osman, OmneyaBertilsson, StefanEiler, Alexander
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