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.
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.
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This Review covers work in the Knight laboratory that is supported by 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.
The authors declare no competing financial interests.
The collection of microbial organisms from a defined environment, such as a human gut.
The collection of genes that are harboured by microbiota.
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.
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.
Sequences that contain repetitions of identical bases.
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.
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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
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