Table 2.

Gut microbiota analysis techniques

Technique16S rRNA Based?Cost ($)Taxonomic Resolution/SensitivityAdvantagesDisadvantages (Limitations)
Culture basedNo$ModerateYou have the organism “in hand”Most GI organisms cannot be cultured in current defined media
Functional information gained from what is known about the organism's substrate utilization and other physiological parametersLabor intensive
Full-length (Sanger) sequencingYes$$$$Very goodSequencing the entire 16S gene maximizes the taxonomic resolution offered by the geneExpensive (although mechanization is reducing the cost)
Extensive bioinformatic analysis required
454 PyrosequencingYes$$$Good to very goodHigher throughput than Sanger sequencing (200,000 sequences versus 20,000)Can't obtain the taxonomic resolution that can be achieved with full-length sequencing
More sensitive (can detect less abundant organisms due to the number of reads obtained)Shorter sequence reads (<500 bp versus 1.5 kb)
Multiple samples can be analyzed in a single sequencing runExtensive bioinformatic analysis required
No cloning bias introduced
Less susceptible to PCR bias (shorter PCR amplicons, less influenced by G/C content)
DGGEYes$PoorRapidShorter PCR products mean less taxonomic information can be obtained
Fingerprints provide a good basis to compare communities from different treatment groupsReproducibility between gels is difficult
Bands of interest can be excised and sequenced
TRFLPYes$$PoorFingerprints provide a good basis to compare communitiesLimited taxonomic resolution
Multiple restriction enzymes can be used to provide greater resolutionOne “phylotype” can represent more than one species
ReproducibleCapillary sequencer required
RISANo$$GoodGreater variability between species and strains than the 16S geneLimited phylogenetic data currently available; no extensive RIS database developed for gut bacteria
When a better database has been developed, taxonomic resolution could be “Excellent”A single bacterium can have more than one different RIS region
DNA microarraysYes$$$$Very goodIncredibly useful as a screening approachDetection limited by the sequences contained on the chip (no detection of uncharacterized phylotypes)
Fast, easy to useCross-hybridization issues
Clinical applications
FISHYes$$$GoodCan target specific bacterial groups/species of interest (they must be preselected)Can't identify novel groups of bacteria
Flexible scope: probes can be designed to target groups or individual speciesIt's not a community-wide survey of “who's there”
Direct enumeration of bacteria- 16S copy number is not an issueReference strains are required to validate the results
Microscope work is time-consuming (however FACS options are becoming available)
qPCRYes$$GoodCan target specific bacterial groups/species of interest (they must be preselected)Reference strains are required to validate the results
Flexible scope: primers can be designed to target groups or individual speciesCan't identify novel groups of bacteria
It's not a community-wide survey of “who's there”
16S copy number varies between 1 and 10
MetagenomicsGenome wide$$$$$GoodProvides a community-wide assessment of the functional genes presentShotgun reads are mapped to reference genomes; this is limited by the number of sequenced genomes available
16S gene sequences provide taxonomic identification of community membersExtensive bioinformatic analysis required
Sensitivity depends on the number of sequence reads obtainedCloning biases could affect the functional gene information obtained
No direct information about which genes are expressed or functioning
MetabolomicsNo$$$$PoorMetabolic profiles can be used to compare communities in a functional contextNo taxonomic information available
More direct functional information can be obtainedThe source of each metabolite is unknown; therefore, it is difficult to identify what organisms are producing what compound
More rapid and less expensive than metagenomicsNot all metabolites are detectable with current technology
Nontargeted approach can also identify host metabolites associated with the gut microbiota
MetaproteomicsNo$$$$PoorMetaproteomes can be used to compare communities in a functional contextNo taxonomic information available
More direct functional information can be obtainedProtein abundance is difficult to estimate
More rapid and less expensive than metagenomicsLess abundant proteins (from populations making up <1% of the community) go undetected
Nontargeted approach can also identify host proteins associated with the gut microbiota
MetatranscriptomicsGenome wide$$$$$GoodProvides insights into community-wide structure and functionRNA is much more easily degraded than DNA; this could cause information loss
Can be used to detect changes in community-wide gene expression profiles in response to different environmental stimuliSensitivity of community analysis depends on the number of sequence reads (via pyrosequencing) obtained
No biases introduced by PCR or cloning steps (none required)
Transcripts can be measured quantitatively
  • A number of techniques have been applied to analyze the composition, abundance, and function of the gastrointestinal microbiota over the last several decades, 16S rRNA-based and otherwise. The analysis method of choice depends on the question being asked as well as the time and cost restrictions associated with the task. An assessment of the benefits and limitations of the current techniques available in gut microbial ecology is provided. GI, gastrointestinal. RIS, ribosomal intergenic spacer.