Experimental and analytical tools for studying the human microbiome

KEY POINTS * New sequencing technologies and open-source computational tools have enabled rapid progress in research into the human microbiota and the human microbiome. * Most recent studies

use _16S_ rDNA gene profiling to assess the organisms that are present in a sample or shotgun metagenomics to get a complete profile of gene content in a given habitat. * Bacterial and

archaeal communities are currently easy to profile using the _16S_ rDNA gene sequence: techniques for profiling eukaryotes and viruses are more challenging but are intense areas of interest.

* Both taxonomic and functional profiling are crucial for obtaining a full picture of the microbiota, although error rates both in sequencing and in functional and taxonomic assignment need

to be considered when drawing conclusions. * Time series studies are proving to be especially useful for understanding variation in the microbiome, as individuals can vary considerably in

their microbiome composition. Thus far, developmental trajectories have only been studied in the gut, although it will be fascinating to extend these studies to other body habitats and to

developmental disorders. * Clustering sequences into taxonomic groups remains challenging, although the quality of current techniques is sufficient to observe clinically relevant differences

among subjects. * Public resources for functional annotation of metagenomic data are expanding rapidly; they are providing key enabling technology for large-scale projects, such as the

Human Microbiome Project and the Earth Microbiome Project. * Studies of the microbiome are rapidly moving from preliminary studies that observe differences among groups to mechanistic and

longitudinal studies that allow us to see how and why these differences develop. Personalized culture collections will be especially important in this respect. ABSTRACT The human microbiome

substantially affects many aspects of human physiology, including metabolism, drug interactions and numerous diseases. This realization, coupled with ever-improving nucleotide sequencing

technology, has precipitated the collection of diverse data sets that profile the microbiome. In the past 2 years, studies have begun to include sufficient numbers of subjects to provide the

power to associate these microbiome features with clinical states using advanced algorithms, increasing the use of microbiome studies both individually and collectively. Here we discuss

tools and strategies for microbiome studies, from primer selection to bioinformatics analysis. Access through your institution Buy or subscribe This is a preview of subscription content,

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MEDICINE Article 18 December 2023 THE GUT MICROBIOME-METABOLOME DATASET COLLECTION: A CURATED RESOURCE FOR INTEGRATIVE META-ANALYSIS Article Open access 15 October 2022 MICROBIOME

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the US National Institutes of Health (NIH), the Bill and Melinda Gates Foundation, the Crohn's and Colitis Foundation and the Howard Hughes Medical Institutes. D.G. was supported by a

grant from the NIH (NIHU54HG004969), the Crohn's and Colitis Foundation of America and the Juvenile Diabetes Research Foundation. AUTHOR INFORMATION AUTHORS AND AFFILIATIONS *

Department of Molecular, Cellular and Developmental Biology, University of Colorado at Boulder, 347 UCB, Boulder, 80309, Colorado, USA Justin Kuczynski & William A. Walters * Cooperative

Institute for Research in Environmental Sciences, University of Colorado at Boulder, 216 UCB, Boulder, 80309, Colorado, USA Christian L. Lauber * Department of Chemistry and Biochemistry,

University of Colorado at Boulder, 215 UCB, Boulder, 80309, Colorado, USA Laura Wegener Parfrey, José C. Clemente & Rob Knight * Microbial Systems & Communities, Genome Sequencing

and Analysis Program, The Broad Institute, 7 Cambridge Center, Cambridge, 02142, Massachusetts, USA Dirk Gevers * Howard Hughes Medical Institute, 215 UCB, Boulder, 80309, Colorado, USA Rob

Knight Authors * Justin Kuczynski View author publications You can also search for this author inPubMed Google Scholar * Christian L. Lauber View author publications You can also search for

this author inPubMed Google Scholar * William A. Walters View author publications You can also search for this author inPubMed Google Scholar * Laura Wegener Parfrey View author publications

You can also search for this author inPubMed Google Scholar * José C. Clemente View author publications You can also search for this author inPubMed Google Scholar * Dirk Gevers View author

publications You can also search for this author inPubMed Google Scholar * Rob Knight View author publications You can also search for this author inPubMed Google Scholar CORRESPONDING

AUTHOR Correspondence to Rob Knight. ETHICS DECLARATIONS COMPETING INTERESTS The authors declare no competing financial interests. RELATED LINKS RELATED LINKS FURTHER INFORMATION Rob

Knight's homepage AmpliconNoise Community Cyberinfrastructure for Advanced Microbial Denoiser Earth Microbiome Project Ecology Research and Analysis (CAMERA) greengenes Human Microbiome

Project Integrated Microbial Genomes with Microbiome samples (IMG/M) MetaHIT MG-RAST mothur _Nature Reviews Genetics_ Series on Study designs _Nature Reviews Genetics_ Series on

Applications of next-generation sequencing QIIME QIIME database Ribosomal Database Project (RDP) SILVA VAMPS Web BLAST page options (details of NCBI's nr database) GLOSSARY * Microbiota

The collection of microbial organisms from a defined environment, such as a human gut. * Microbiome The collection of genes that are harboured by microbiota. * Metagenomics The study of the

collective genome of microorganisms from an environment. Shotgun metagenomics refers to the approach of shearing DNA that have been extracted from the environment and sequencing the small

fragments. * Amplicon An amplified fragment of DNA from a region of a marker gene (such as _16S_ rDNA) that is generated by PCR. * Bead beating A process used to lyse cells and to disrupt

larger structures before DNA extraction. * Paired-end sequencing An approach used in some sequencing platforms in which a single DNA clone is subjected to sequencing reads that originate

from each of a set of primers, such that the direction of each sequencing reaction is directed to the origin of the other. * Functional profiling approaches Studies in which the genomic DNA

of the microbiome is assessed for functional potential. * Jumping libraries Libraries that use molecular biology techniques to join together the ends of a larger DNA fragment, allowing

sequencing on platforms that can only sequence a shorter fragment length. For example, 10 kb fragments might be reduced to 200 bases from each end, giving a final fragment size of 400 bp

that can undergo paired-end sequencing. * Operational taxonomic units (OTUs). Sequences are generally collapsed into OTUs based on sequence similarity thresholds for downstream analyses. The

typical threshold is 97%, and this is taken as a proxy for species level divergence, although what constitutes a microbial species remains an open debate. * Chimeric sequence An artificial

sequence that juxtaposes gene regions from two or more unrelated organisms. It is produced by recombination between two or more DNA molecules during PCR amplification. * Homopolymers

Sequences that contain repetitions of identical bases. * Metadata Information associated with sequences, including environmental conditions and the time and location of the sample collection

site. * Principal coordinates analysis (PCoA). A multivariate technique used in microbiome studies to visualize the relationships among communities. Each community is represented by a point

in typically two- or three-dimensional space, and similar communities are located close to one another in the resulting PCoA plot. * Rarefaction curves Plots of community diversity versus

depth of sequencing (or, generally, observation). They are used to assess the amount of diversity and the extent to which it has been sampled at a given depth of sequencing. * Interpolated

Markov models A bioinformatics technique used here to classify DNA sequences using patterns of _k_-mer nucleotide strings that are present in a within a genome database. * Leave-one-out

analyses Studies of a microbial community that lacks one of its constituent microbial taxa. RIGHTS AND PERMISSIONS Reprints and permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Kuczynski,

J., Lauber, C., Walters, W. _et al._ Experimental and analytical tools for studying the human microbiome. _Nat Rev Genet_ 13, 47–58 (2012). https://doi.org/10.1038/nrg3129 Download citation

* Published: 16 December 2011 * Issue Date: January 2012 * DOI: https://doi.org/10.1038/nrg3129 SHARE THIS ARTICLE Anyone you share the following link with will be able to read this content:

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